Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Rudin, C. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0048-x · Cited by 10,561 · see citing works

High-performance medicine: the convergence of human and artificial intelligence

Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450 · see citing works

A guide to deep learning in healthcare

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0316-z · Cited by 5,312 · see citing works

A New Initiative on Precision Medicine

Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works

Shared decision making — The pinnacle of patient-centered care

Barry, M. J., & Edgman-Levitan, S. (2012) · New England Journal of Medicine · doi:10.1056/nejmp1109283 · Cited by 3,433 · see citing works

Deep learning for healthcare: review, opportunities and challenges

Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bbx044 · Cited by 3,076 · see citing works

XAI—Explainable artificial intelligence

Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., & Yang, G.-Z. (2019) · Science Robotics · doi:10.1126/scirobotics.aay7120 · Cited by 2,053 · see citing works

Deep Learning for Health Informatics

Ravì, D., Wong, C., Deligianni, F., Berthelot, M., Andreu-Perez, J., Lo, B., & Yang, G.-Z. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2636665 · Cited by 2,000 · see citing works

Machine Learning and Prediction in Medicine — Beyond the Peak of Inflated Expectations

Chen, J. H., & Asch, S. M. (2017) · New England Journal of Medicine · doi:10.1056/nejmp1702071 · Cited by 1,171 · see citing works

Internet Health Information Seeking and the Patient-Physician Relationship: A Systematic Review

Tan, S. S.-L., & Goonawardene, N. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.5729 · Cited by 1,101 · see citing works

Clinical decision support in the era of artificial intelligence

Shortliffe, E. H., & Sepúlveda, M. J. (2018) · JAMA · doi:10.1001/jama.2018.17163 · Cited by 920 · see citing works

Cognitive and usability engineering methods for the evaluation of clinical information systems.

Kushniruk, A. W., & Patel, V. L. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.01.003 · Cited by 760 · see citing works

Deep Learning—A Technology With the Potential to Transform Health Care

Hinton, G. (2018) · JAMA · doi:10.1001/jama.2018.11100 · Cited by 667 · see citing works

The importance of interpretability and visualization in machine learning for applications in medicine and health care

Vellido, A. (2020) · Neural Computing and Applications · doi:10.1007/s00521-019-04051-w · Cited by 635 · see citing works

Using usability heuristics to evaluate patient safety of medical devices

Zhang, J., Johnson, T. R., Patel, V. L., Paige, D. L., & Kubose, T. (2003) · Journal of Biomedical Informatics · doi:10.1016/s1532-0464(03)00060-1 · Cited by 591 · see citing works

Using electronic health records for population health research: a review of methods and applications

Casey, J. A., Schwartz, B. S., Stewart, W. F., & Adler, N. E. (2016) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-032315-021353 · Cited by 590 · see citing works

The Emergence of National Electronic Health Record Architectures in the United States and Australia: Models, Costs, and Questions

Gunter, T. D., & Terry, N. P. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e3 · Cited by 440 · see citing works

A user-centered framework for redesigning health care interfaces

Johnson, C., Johnson, T. R., & Zhang, J. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.11.005 · Cited by 379 · see citing works

Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis

Khairat, S., Marc, D. T., Crosby, W., & Sanousi, A. A. (2018) · JMIR Medical Informatics · doi:10.2196/medinform.8912 · Cited by 336 · see citing works

TURF: Toward a unified framework of EHR usability

Zhang, J., & Walji, M. F. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.08.005 · Cited by 301 · see citing works

Improving Outcomes with Clinical Decision Support : An Implementer's Guide

Osheroff, J. A., Teich, J. M., Levick, D., Saldana, L., Velasco, F. T., Sittig, D. F., Rogers, K. M., & Jenders, R. A. (2012) · Cited by 297 · see citing works

Interface design principles for usable decision support: A targeted review of best practices for clinical prescribing interventions

Horsky, J., Schiff, G. D., Johnston, D., Mercincavage, L. M., Bell, D. S., & Blackford Middleton, A. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.09.002 · Cited by 290 · see citing works

Patients’ views of wearable devices and AI in healthcare: findings from the ComPaRe e-cohort

Tran, V.-T., Riveros, C., & Ravaud, P. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0132-y · Cited by 266 · see citing works

Clinical Decision Support: The Road Ahead

Greenes, R. A. (2006) · Cited by 261 · see citing works

Using HL7 FHIR to achieve interoperability in patient health record

Saripalle, R. K., Runyan, C., & Mitchell, R. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103188 · Cited by 259 · see citing works

On the Prospects for a (Deep) Learning Health Care System

Naylor, C. D. (2018) · JAMA · doi:10.1001/jama.2018.11103 · Cited by 250 · see citing works

Improving Healthcare with Interactive Visualization

Shneiderman, B., Catherine Plaisant, B., & Hesse, B. W. (2013) · Computer · doi:10.1109/mc.2013.38 · Cited by 191 · see citing works

Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS

Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. S. H. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.11.012 · Cited by 185 · see citing works

Using qualitative studies to improve the usability of an EMR

Rose, A. F., Schnipper, J. L., Park, E. R., Poon, E. G., Li, Q., & Blackford Middleton, A. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.11.006 · Cited by 169 · see citing works

Translational cognition for decision support in critical care environments: A review

Patel, V. L., Zhang, J., Yoskowitz, N. A., Green, R., & Sayan, O. R. (2008) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2008.01.013 · Cited by 143 · see citing works

Text mining approach to predict hospital admissions using early medical records from the emergency department

Lucini, F. R., Fogliatto, F. S., da Silveira, G. J. C., Neyeloff, J. L., Anzanello, M. J., Kuchenbecker, R. S., & Schaan, B. D. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.01.001 · Cited by 139 · see citing works

Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT

Deist, T. M., Jochems, A., van Soest, J., Nalbantov, G. I., Oberije, C., Walsh, S., Eble, M. J., Bulens, P., Coucke, P. A., Dries, W., et al. (2017) · Clinical and Translational Radiation Oncology · doi:10.1016/j.ctro.2016.12.004 · Cited by 139 · see citing works

Fake Cures

Ghenai, A., & Mejova, Y. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274327 · Cited by 127 · see citing works

Dashboard visualizations: Supporting real-time throughput decision-making

Franklin, A., Gantela, S., Shifarraw, S., Johnson, T. R., Robinson, D. J., King, B. R., Mehta, A. M., Maddow, C. L., Hoot, N. R., Nguyen, V., et al. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.05.024 · Cited by 126 · see citing works

Electronic health record: Wiring Europe’s healthcare

Kierkegaard, P. (2011) · Computer law & security review · doi:10.1016/j.clsr.2011.07.013 · Cited by 122 · see citing works

Patients' and physicians' understanding of health and biomedical concepts: relationship to the design of EMR systems

Patel, V. L., Arocha, J. F., & Kushniruk, A. W. (2002) · Journal of Biomedical Informatics · doi:10.1016/s1532-0464(02)00002-3 · Cited by 119 · see citing works

Identifying reasoning strategies in medical decision making: A methodological guide

Arocha, J. F., Wang, D., & Patel, V. L. (2005) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.02.001 · Cited by 117 · see citing works

User-centered design to improve clinical decision support in primary care

Brunner, J., Chuang, E., Goldzweig, C. L., Cain, C., Sugar, C. A., & Yano, E. M. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.05.004 · Cited by 117 · see citing works

“Think aloud” and “Near live” usability testing of two complex clinical decision support tools

Richardson, S. I., Mishuris, R. G., O’Connell, A., Feldstein, D., Hess, R., Smith, P. R., McCullagh, L., McGinn, T. G., & Mann, D. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.06.003 · Cited by 116 · see citing works

Project HealthDesign: Rethinking the power and potential of personal health records

Brennan, P. F., Downs, S. J., & Casper, G. R. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2010.09.001 · Cited by 112 · see citing works

Analysis of Complex Decision-Making Processes in Health Care: Cognitive Approaches to Health Informatics

Kushniruk, A. W. (2001) · Journal of Biomedical Informatics · doi:10.1006/jbin.2001.1021 · Cited by 110 · see citing works

Medical errors as a result of specialization

Hashem, A., Michelene, T. H., & Friedman, C. P. (2003) · Journal of Biomedical Informatics · doi:10.1016/s1532-0464(03)00057-1 · Cited by 107 · see citing works

Paving the COWpath: Learning and visualizing clinical pathways from electronic health record data

Zhang, Y., Padman, R., & Patel, N. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.09.009 · Cited by 103 · see citing works

Accuracy is in the eyes of the pathologist: The visual interpretive process and diagnostic accuracy with digital whole slide images

Brunyé, T. T., Mercan, E., Weaver, D. L., & Elmore, J. G. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.01.004 · Cited by 94 · see citing works

Assessment of a personalized and distributed patient guidance system

Mor Peleg, B., D, Y. S. M., Quaglini, S., Broens, T., Budasu, R., Fung, N. L. S., Fux, A., García-Sáez, G., Goldstein, A., González-Ferrer, A., et al. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.02.010 · Cited by 87 · see citing works

Design and development of a mobile computer application to reengineer workflows in the hospital and the methodology to evaluate its effectiveness

Holzinger, A., Kosec, P., Schwantzer, G., Debevc, M., Hofmann‐Wellenhof, R., & Frühauf, J. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.07.003 · Cited by 86 · see citing works

Joint modeling of heterogeneous sensing data for depression assessment via multi-task learning

Lu, J., Shang, C., Yue, C., Morillo, R., Ware, S., Kamath, J., Bamis, A., Russell, A., Wang, B., & Bi, J. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3191753 · Cited by 85 · see citing works

Eye tracking measures of uncertainty during perceptual decision making

Brunyé, T. T., & Gardony, A. L. (2017) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2017.07.008 · Cited by 81 · see citing works

Opportunistic decision making and complexity in emergency care

Franklin, A., Liu, Y., Li, Z., Nguyen, V., Johnson, T. R., Robinson, D. J., Okafor, N. G., King, B. R., Patel, V. L., & Zhang, J. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.04.001 · Cited by 79 · see citing works

Medical Data Processing and Analysis for Remote Health and Activities Monitoring

Vitabile, S., Marks, M., Stojanovic, D. H., Sabri Pllana, A., Molina, J. M., Krzysztoń, M., Sikora, A., Jarynowski, A. K., Hosseinpour, F., Jakóbik, A., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-16272-6_7 · Cited by 75 · see citing works

Understanding infusion administration in the ICU through Distributed Cognition

Rajkomar, A., & BLANDFORD, A. E. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.02.003 · Cited by 74 · see citing works

Cognitive simulators for medical education and training

Kahol, K., Vankipuram, M., & Smith, M. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.02.008 · Cited by 68 · see citing works

Scenarios, personas and user stories: User-centered evidence-based design representations of communicable disease investigations

Turner, A. M., Reeder, B., & Ramey, J. A. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.04.006 · Cited by 67 · see citing works

Assessment of a medical information system: the mediating role of use and user satisfaction on the success of human interaction with the mobile healthcare system (iHeart)

Keikhosrokiani, P., Mustaffa, N., Zakaria, N., & Abdullah, R. (2019) · Cognition Technology & Work · doi:10.1007/s10111-019-00565-4 · Cited by 67 · see citing works

User-designed information tools to support communication and care coordination in a trauma hospital

Gürses, A. P., Xiao, Y., & Hu, P. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.03.007 · Cited by 65 · see citing works

Design of a Decision-Support Architecture for Management of Remotely Monitored Patients

Basilakis, J., Lovell, N. H., Redmond, S. J., & Celler, B. G. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2055881 · Cited by 63 · see citing works

MobiGuide: a personalized and patient-centric decision-support system and its evaluation in the atrial fibrillation and gestational diabetes domains

Mor Peleg, B., D, Y. S. M., Quaglini, S., Fux, A., García-Sáez, G., Goldstein, A., Hernando, M. E., Klimov, D., Martínez-Sarriegui, I., Napolitano, C., et al. (2017) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-017-9190-5 · Cited by 63 · see citing works

Prescriber response to computerized drug alerts for electronic prescriptions among hospitalized patients

Zenziper, Y., Kurnik, D., Matok, I., Halkin, H., Markovits, N., Ziv, A., Shamiss, A., & Loebstein, R. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.08.008 · Cited by 63 · see citing works

Information system design for a hospital emergency department: A usability analysis of software prototypes

Adem Karahoca, A., Bayraktar, E., Tatoğlu, E., & Karahoca, D. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2009.09.002 · Cited by 62 · see citing works

Improving diagnostic accuracy using EHR in emergency departments: A simulation-based study

Ben‐Assuli, O., Sagi, D., Leshno, M., Ironi, A., & Ziv, A. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.03.004 · Cited by 61 · see citing works

Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information

Vest, J. R., & Ben-Assuli, O. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.06.013 · Cited by 61 · see citing works

Do multidisciplinary cancer care teams suffer decision-making fatigue: an observational, longitudinal team improvement study

Soukup, T., Gandamihardja, T., McInerney, S., Green, J. S. A., & Sevdalis, N. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-027303 · Cited by 59 · see citing works

A Multi-step Usability Evaluation of a Self-Management App to Support Medication Adherence in Persons Living with HIV

Beauchemin, M., Gradilla, M., Baik, D., Cho, H., & Schnall, R. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.11.012 · Cited by 58 · see citing works

Getting to the point: developing IT for the sharp end of healthcare

Nemeth, C., Nunnally, M., O’Connor, M., Klock, P. A., & Cook, R. (2005) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.11.002 · Cited by 57 · see citing works

Experiences, practices and barriers to accessing health information: A qualitative study

Scantlebury, A., Booth, A., & Hanley, B. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.04.018 · Cited by 57 · see citing works

Recovery at the edge of error: Debunking the myth of the infallible expert

Patel, V. L., Cohen, T., Murarka, T., Olsen, J., Kagita, S., Myneni, S., Buchman, T. G., & Ghaemmaghami, V. (2010) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2010.09.005 · Cited by 56 · see citing works

Critical Care Health Informatics Collaborative (CCHIC): Data, tools and methods for reproducible research: A multi-centre UK intensive care database

Harris, S. K., Shi, S., Brealey, D. A., MacCallum, N. S., Denaxas, S., Pérez–Suárez, D., Ercole, A., Watkinson, P., Jones, A., Ashworth, S., et al. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.01.006 · Cited by 56 · see citing works

VisualDecisionLinc: A visual analytics approach for comparative effectiveness-based clinical decision support in psychiatry

Mane, K. K., Bizon, C., Schmitt, C., Owen, P., Burchett, B. M., Pietrobon, R. S., & Gersing, K. R. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.09.003 · Cited by 53 · see citing works

A Shared Decision-Making System for Diabetes Medication Choice Utilizing Electronic Health Record Data

Wang, Y., Li, P., Tian, Y., Ren, J., & Li, J. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2614991 · Cited by 51 · see citing works

Just-in-Time but Not Too Much

Liao, P., Dempsey, W., Sarker, H., Hossain, S. M., Al’Absi, M., Klasnja, P., & Murphy, S. A. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3287057 · Cited by 50 · see citing works

A Survey on Nature-Inspired Medical Image Analysis: A Step Further in Biomedical Data Integration

Rundo, L., Militello, C., Vitabile, S., Russo, G. I., Sala, E., & Gilardi, M. C. (2019) · Fundamenta Informaticae · doi:10.3233/fi-2020-1887 · Cited by 49 · see citing works

icuARM-An ICU Clinical Decision Support System Using Association Rule Mining

Cheng, C., Chanani, N. K., Venugopalan, J., Maher, K. O., & Wang, M. D. (2013) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2013.2290113 · Cited by 47 · see citing works

A cardiovascular simulator tailored for training and clinical uses

Fresiello, L., Ferrari, G., Molfetta, A. D., Zieliński, K., Tzallas, A. T., Jacobs, S., Darowski, M., Kozarski, M., Meyns, B. P., Katertsidis, N. S., et al. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.07.004 · Cited by 43 · see citing works

An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation

Shalom, E., Shaḥar, Y., & Lunenfeld, E. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.11.006 · Cited by 43 · see citing works

A data-driven and practice-based approach to identify risk factors associated with hospital-acquired falls: Applying manual and semi- and fully-automated methods

Lucero, R. J., Lindberg, D. S., Fehlberg, E. A., Bjarnadóttir, R. I., Yin, L., Cimiotti, J. P., Crane, M., & Prosperi, M. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.11.006 · Cited by 42 · see citing works

Cognitive Informatics for Biomedicine

(2015) · Health informatics · doi:10.1007/978-3-319-17272-9 · Cited by 38 · see citing works

Cognitive factors influencing perceptions of clinical documentation tools

Rosenbloom, S. T., Crow, A. N., Blackford, J. U., & Johnson, K. B. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.06.006 · Cited by 37 · see citing works

WhatsApp Use In The Evaluation of Hematuria

Şener, T. E., Butticè, S., Şahin, B., Netsch, C., Dragos, L. B., Pappalardo, R., & Magno, C. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.12.011 · Cited by 37 · see citing works

Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study

Sung, S., Chen, K., Wu, D. P., Hung, L.-C., Su, Y.-H., & Hu, Y. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.02.005 · Cited by 37 · see citing works

Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record

Payne, T. H., Alonso, W. D., Markiel, J. A., Lybarger, K., & White, A. A. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.12.004 · Cited by 36 · see citing works

Sharing clinical decisions for multimorbidity case management using social network and open-source tools

Martínez-García, A., Moreno-Conde, A., Sánchez, F. J., Leal, S., & Parra, C. L. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.06.007 · Cited by 35 · see citing works

EHRs, Meaningful Use, and a Model EMR

Habib, J. (2010) · Cited by 35 · see citing works

Clinical Decision Support System for Liver Fibrosis Prediction in Hepatitis Patients: A Case Comparison of Two Soft Computing Techniques

El–Sappagh, S., Ali, F., Ali, A., Hendawi, A., Badria, F. A.-E., & Suh, D. Y. (2018) · IEEE Access · doi:10.1109/access.2018.2868802 · Cited by 33 · see citing works

Natural language processing of German clinical colorectal cancer notes for guideline-based treatment evaluation

Becker, M., Kasper, S., Böckmann, B., Jöckel, K., & Virchow, I. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.04.022 · Cited by 33 · see citing works

Usability of a novel clinician interface for genetic results

Neri, P. M., Pollard, S. E., Volk, L. A., Newmark, L. P., Varugheese, M., Baxter, S. M., Aronson, S., Rehm, H. L., & Bates, D. W. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.03.007 · Cited by 32 · see citing works

Adaptive support for user interface customization: a study in radiology

Jorritsma, W., Cnossen, F., & van Ooijen, P. M. A. (2015) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2014.12.008 · Cited by 32 · see citing works

A framework for data-driven adaptive GUI generation based on DICOM

Gambino, O., Rundo, L., Cannella, V., Vitabile, S., & Pirrone, R. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.10.009 · Cited by 31 · see citing works

Designing the design phase of critical care devices: a cognitive approach

Malhotra, S., Laxmisan, A., Keselman, A., Zhang, J., & Patel, V. L. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.11.001 · Cited by 30 · see citing works

A computer-human interaction model to improve the diagnostic accuracy and clinical decision-making during 12-lead electrocardiogram interpretation

Cairns, A. W., Bond, R., Finlay, D., Breen, C. J., Guldenring, D., Gaffney, R., Gallagher, A. G., Peace, A. J., & Henn, P. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.09.016 · Cited by 30 · see citing works

Feasibility study of an EHR-integrated mobile shared decision making application

Day, F. C., Pourhomayoun, M., Keeves, D., Lees, A. F., Sarrafzadeh, M., Bell, D. S., & Pfeffer, M. A. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.01.008 · Cited by 30 · see citing works

Physicians’ perceptions of the impact of the EHR on the collection and retrieval of psychosocial information in outpatient diabetes care

Senteio, C. R., Veinot, T. C., Adler‐Milstein, J., & Richardson, C. R. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.02.003 · Cited by 29 · see citing works

Multi-method laboratory user evaluation of an actionable clinical performance information system: Implications for usability and patient safety

Brown, B. C., Balatsoukas, P., Williams, R., Sperrin, M., & Buchan, I. E. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.11.008 · Cited by 28 · see citing works

Merits of usability testing for PACS selection

Jorritsma, W., Cnossen, F., & van Ooijen, P. M. A. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.10.003 · Cited by 27 · see citing works

A cognitive systems engineering design approach to improve the usability of electronic order forms for medical consultation

Savoy, A., Militello, L. G., Patel, H., Flanagan, M., Russ, A. L., Daggy, J., Weiner, M., & Saleem, J. J. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.07.021 · Cited by 27 · see citing works

Heuristic evaluation and simulated use testing of infusion pumps to inform pump selection

Liu, K., Chan, F.-Y., Or, C. K., Sun, D. T., Lai, W.-S., & So, H. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.07.011 · Cited by 27 · see citing works

The role of computerized diagnostic proposals in the interpretation of the 12-lead electrocardiogram by cardiology and non-cardiology fellows

Novotný, T., Bond, R., Andršová, I., Koc, L., Šišáková, M., Finlay, D., Guldenring, D., Špinar, J., & Malík, M. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.02.007 · Cited by 25 · see citing works

Biomedical Ontology Quality Assurance Using a Big Data Approach

Cui, L., Tao, S., & Zhang, G. (2016) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2768830 · Cited by 24 · see citing works

Integration of an in-home monitoring system into home care nurses’ workflow: A case study

Klemets, J., Määttälä, J., & Hakala, I. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.12.006 · Cited by 24 · see citing works

Using machine learning to selectively highlight patient information

King, A. J., Cooper, G. F., Clermont, G., Hochheiser, H., Hauskrecht, M., Sittig, D. F., & Visweswaran, S. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103327 · Cited by 24 · see citing works

Discovering Design Principles for Health Behavioral Change Support Systems

Al-Ramahi, M. A., Liu, J., & El-Gayar, O. (2017) · ACM Transactions on Management Information Systems · doi:10.1145/3055534 · Cited by 23 · see citing works

The ALMANACH Project: Preliminary results and potentiality from Afghanistan

Bernasconi, A. R., Crabbé, F., Rossi, R., Qani, I., Vanobberghen, A., Raab, M., & Mortier, S. D. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.12.021 · Cited by 23 · see citing works

Avatar-based simulation in the evaluation of diagnosis and management of mental health disorders in primary care

Satter, R. M., Cohen, T., Ortiz, P., Kahol, K., Mackenzie, J., Olson, C., Johnson‐Glenberg, M. C., & Patel, V. L. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.07.009 · Cited by 22 · see citing works

Decisions about critical events in device-related scenarios as a function of expertise

Laxmisan, A., Malhotra, S., Keselman, A., Johnson, T. R., & Patel, V. L. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.11.012 · Cited by 21 · see citing works

Interactive data visualization based on conventional statistical findings for antihypertensive prescriptions using National Health Insurance claims data

Ko, I., & Chang, H. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.05.003 · Cited by 21 · see citing works

Identification and classification of DICOM files with burned-in text content

Včelák, P., Kryl, M., Kratochvíl, M., & Klečková, J. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.02.011 · Cited by 21 · see citing works

Assisting radiologists with reporting urgent findings to referring physicians: A machine learning approach to identify cases for prompt communication

Meng, X., Ganoe, C. H., Sieberg, R. T., Cheung, Y. Y., & Hassanpour, S. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103169 · Cited by 21 · see citing works

Supervised methods to extract clinical events from cardiology reports in Italian

Viani, N., Miller, T. A., Napolitano, C., Priori, S. G., Savova, G., Bellazzi, R., & Sacchi, L. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103219 · Cited by 21 · see citing works

Health information management practices in informal caregiving: An artifacts analysis and implications for IT design

Holden, R. J., Karanam, Y., Cavalcanti, L., Parmar, T., Kodthala, P., Fowler, N. R., & Bateman, D. R. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.09.017 · Cited by 20 · see citing works

Ontological modeling of electronic health information exchange

McMurray, J., Zhu, L., McKillop, I., & Chen, H. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.05.020 · Cited by 19 · see citing works

Decision support for acute problems: The role of the standardized patient in usability testing

Linder, J. A., Rose, A. F., Palchuk, M. B., CHANG, F. Y., Schnipper, J. L., Chan, J. C., & Blackford Middleton, A. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.12.002 · Cited by 19 · see citing works

Identifying and prioritizing the tools/techniques of knowledge management based on the Asian Productivity Organization Model (APO) to use in hospitals

Khajouei, H., & Khajouei, R. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.10.012 · Cited by 19 · see citing works

MechanicalHeart

Callaghan, W., Goh, J., Mohareb, M. M., Lim, A. S. P., & Law, E. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274297 · Cited by 19 · see citing works

Human-Computer Interaction in Electronic Medical Records: From the Perspectives of Physicians and Data Scientists

Bologva, E. V., Prokusheva, D. I., Krikunov, A. V., Звартау, Н. Э., & Kovalchuk, S. V. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.09.248 · Cited by 18 · see citing works

Translating research into practice through user-centered design: An application for osteoarthritis healthcare planning

Carr, E., Babione, J., & Marshall, D. A. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.05.007 · Cited by 18 · see citing works

The use of computerized physician order entry with clinical decision support reduces practice variance in ordering preoperative investigations: A retrospective cohort study

Sim, E. Y., Tan, D. J. A., & Abdullah, H. R. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.09.015 · Cited by 18 · see citing works

POPCORN: A web service for individual PrognOsis prediction based on multi-center clinical data CollabORatioN without patient-level data sharing

Tian, Y., Shang, Y., Tong, D., Chi, S., Li, J., Kong, X., Ding, K., & Li, J. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.08.008 · Cited by 17 · see citing works

A dialogue-based approach for dealing with uncertain and conflicting information in medical diagnosis

Yan, C., Lindgren, H., & Nieves, J. C. (2018) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-018-9396-x · Cited by 16 · see citing works

Justifying diagnosis decisions by deep neural networks

Spinks, G., & Moens, M. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103248 · Cited by 16 · see citing works

A distributed system for support and explanation of shared decision-making in the prenatal testing domain

Segal, I., & D, Y. S. M. (2008) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2008.09.004 · Cited by 15 · see citing works

Refining an Automatic EDSS Scoring Expert System for Routine Clinical Use in Multiple Sclerosis

Gáspari, M., Saletti, D., Scandellari, C., & Stecchi, S. (2009) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2008.926498 · Cited by 15 · see citing works

Assessing and comparing the usability of Chinese EHRs used in two Peking University hospitals to EHRs used in the US: A method of RUA

Xu, L., Wen, D., Zhang, X., & Lei, J. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.02.008 · Cited by 15 · see citing works

Supporting biomedical ontology evolution by identifying outdated concepts and the required type of change

Cardoso, S. D., Pruski, C., & Silveira, M. D. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.08.013 · Cited by 15 · see citing works

Creating synthetic patient data to support the design and evaluation of novel health information technology

Pollack, A. H., Simon, T. D., Snyder, J., & Pratt, W. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103201 · Cited by 15 · see citing works

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring

Aselmaa, A., van Herk, M., Laprie, A., Nestle, U., Götz, I., Wiedenmann, N. E., Schimek‐Jasch, T., Picaud, F., Syrykh, C., Cagetti, L. V., et al. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.12.001 · Cited by 14 · see citing works

Clinical decision support tool for Co-management signalling

Horta, A. B., Salgado, C. M., Fernandes, M. P., Vieira, S. M., Sousa, J. M. C., Papoila, A. L., & Xavier, M. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.02.014 · Cited by 14 · see citing works

Design of a clinician dashboard to facilitate co-decision making in the management of non-specific low back pain

Bach, K., Marling, C., Mork, P. J., Aamodt, A., Mair, F. S., & Nicholl, B. I. (2018) · Journal of Intelligent Information Systems · doi:10.1007/s10844-018-0539-y · Cited by 14 · see citing works

Cognitive requirements for primary care providers during the referral process: Information needed from and interactions with an electronic health record system

Savoy, A., Militello, L. G., Diiulio, J., Midboe, A. M., Weiner, M., Abbaszadegan, H., & Herout, J. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.05.027 · Cited by 13 · see citing works

Automatic identification of recent high impact clinical articles in PubMed to support clinical decision making using time-agnostic features

Bian, J., Abdelrahman, S., Shi, J., & Fiol, G. D. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.11.010 · Cited by 11 · see citing works

Emotional Awareness and Decision-Making in the Context of Computer-Mediated Psychotherapy

Alvandi, E. O., Doorn, G. H. V., & Symmons, M. A. (2019) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-019-00050-7 · Cited by 9 · see citing works

DecisionMind: revealing human cognition states in data analytics-driven decision making with a multimodal interface

Zhou, J. J., & Chen, F. (2017) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-017-0249-8 · Cited by 8 · see citing works

Digital video analysis of health professionals’ interactions with an electronic whiteboard: A longitudinal, naturalistic study of changes to user interactions

Rasmussen, R. O., & Kushniruk, A. W. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.08.002 · Cited by 6 · see citing works

Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies

Safari, L., & Patrick, J. D. (2018) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2018.04.004 · Cited by 4 · see citing works

Identifying patient-related information problems: A study of information use by patient-care teams during morning rounds

Murphy, A. R., & Reddy, M. C. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.03.010 · Cited by 3 · see citing works

An enhancement on Clinical Data Analytics Language (CliniDAL) by integration of free text concept search

Safari, L., & Patrick, J. D. (2018) · Journal of Intelligent Information Systems · doi:10.1007/s10844-018-0503-x · Cited by 3 · see citing works

Cloud-based image sharing network for collaborative imaging diagnosis and consultation

Yang, Y., Zhang, J., Gu, Y., Wang, M., Li, M., Zhang, W., & Sun, J. (2018) · SPIE Medical Imaging: Imaging Informatics for Healthcare, Research, and Applications · doi:10.1117/12.2293285 · Cited by 3 · see citing works

Imaging Biomarker Ontology (IBO): A Biomedical Ontology to Annotate and Share Imaging Biomarker Data

Amdouni, E., & Gibaud, B. (2018) · Journal on Data Semantics · doi:10.1007/s13740-018-0093-3 · Cited by 3 · see citing works

POP-PL

Florence, S. P., Fetscher, B., Flatt, M., Temps, W., St-Amour, V., Kiguradze, T., West, D., Niznik, C. M., Yarnold, P., Findler, R., et al. (2018) · ACM Transactions on Programming Languages and Systems · doi:10.1145/3210256 · Cited by 2 · see citing works

Improving Outcomes with Clinical Decision Support

Osheroff, J. A., Teich, J., Levick, D., et al. (2020) · HIMSS Publishing eBooks · doi:10.4324/9780367806125

AI applications to medical images: From machine learning to deep learning

Castiglioni, I., Rundo, L., Codari, M., Leo, G. D., Salvatore, C., Interlenghi, M., Gallivanone, F., Cozzi, A., D’Amico, N. C., & Sardanelli, F. (2021) · Physica Medica · doi:10.1016/j.ejmp.2021.02.006 · Cited by 737 · see citing works

Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review

Antoniadi, A. M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B. A., & Mooney, C. (2021) · Applied Sciences · doi:10.3390/app11115088 · Cited by 629 · see citing works

Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions

Chengoden, R., Victor, N., Huynh‐The, T., Yenduri, G., Jhaveri, R. H., Alazab, M., Bhattacharya, S., Hegde, P., Maddikunta, P. K. R., & Gadekallu, T. R. (2023) · IEEE Access · doi:10.1109/access.2023.3241628 · Cited by 551 · see citing works

A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom

Shaik, T., Tao, X., Li, L., Xie, H., & Velasquez, J. D. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.102040 · Cited by 213 · see citing works

Data Integration Challenges for Machine Learning in Precision Medicine

Martínez-García, M., & Hernández-Lemus, E. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2021.784455 · Cited by 158 · see citing works

A Review on the Application of Internet of Medical Things in Wearable Personal Health Monitoring: A Cloud-Edge Artificial Intelligence Approach

Putra, K. T., Arrayyan, A. Z., Hayati, N. Q., Firdaus, F., Damarjati, C., Bakar, A., & Chen, H. (2024) · IEEE Access · doi:10.1109/access.2024.3358827 · Cited by 147 · see citing works

CoAID-DEEP: An Optimized Intelligent Framework for Automated Detecting COVID-19 Misleading Information on Twitter

AbdElminaam, D. S., Ismail, F. H., Taha, M., Taha, A., Houssein, E. H., & Nabil, A. M. (2021) · IEEE Access · doi:10.1109/access.2021.3058066 · Cited by 140 · see citing works

Systematic Review on AI-Blockchain Based E-Healthcare Records Management Systems

Haddad, A., Habaebi, M. H., Islam, M. R., Hasbullah, N. F., & Zabidi, S. A. (2022) · IEEE Access · doi:10.1109/access.2022.3201878 · Cited by 147 · see citing works

Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

Uddin, R., & Koo, I. (2024) · Applied Sciences · doi:10.3390/app14051876 · Cited by 118 · see citing works

Image biomarkers and explainable AI: handcrafted features versus deep learned features

Rundo, L., & Militello, C. (2024) · European Radiology Experimental · doi:10.1186/s41747-024-00529-y · Cited by 101 · see citing works

Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System

Rajashekar, N., Shin, Y. E., Pu, Y., Chung, S., You, K., Giuffrè, M., Chan, C., Saarinen, T., Hsiao, A., Sekhon, J. S., et al. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642024 · Cited by 96 · see citing works

Essential properties and explanation effectiveness of explainable artificial intelligence in healthcare: A systematic review

Jung, J., Lee, H., Jung, H., & Kim, H. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e16110 · Cited by 87 · see citing works

Decades on emergency decision-making: a bibliometric analysis and literature review

Hou, L.-X., Mao, L.-X., Liu, H.-C., & Zhang, L. (2021) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00451-5 · Cited by 58 · see citing works

Semi-automated and interactive segmentation of contrast-enhancing masses on breast DCE-MRI using spatial fuzzy clustering

Militello, C., Rundo, L., Dimarco, M., Orlando, A. A. M., Conti, V., Woitek, R., D’Angelo, I., Bartolotta, T. V., & Russo, G. I. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.103113 · Cited by 61 · see citing works

Designing explainable AI to improve human-AI team performance: A medical stakeholder-driven scoping review

Subramanian, H. V., Canfield, C., & Shank, D. B. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102780 · Cited by 67 · see citing works

The use of AI in mental health services to support decision-making: scoping review

Auf, H., Svedberg, P., Nygren, J., Nair, M., & Lundgren, L. E. (2025) · Journal of Medical Internet Research · doi:10.2196/63548 · Cited by 56 · see citing works

Artificial intelligence in clinical and translational science: Successes, challenges and opportunities

Bernstam, E. V., Shireman, P. K., Meric‐Bernstam, F., Zozus, M. N., Jiang, X., Brimhall, B. B., Windham, A. K., Schmidt, S., Visweswaran, S., Ye, Y., et al. (2021) · Clinical and Translational Science · doi:10.1111/cts.13175 · Cited by 54 · see citing works

CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease

Militello, C., Prinzi, F., Sollami, G., Rundo, L., Grutta, L. L., & Vitabile, S. (2023) · Cognitive Computation · doi:10.1007/s12559-023-10118-7 · Cited by 52 · see citing works

GLA-Net: A global-local attention network for automatic cataract classification

Xu, X., Li, J., Guan, Y., Zhao, L., Zhao, Q., Zhang, L., & Li, L. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103939 · Cited by 50 · see citing works

Can technological advancements help to alleviate COVID-19 pandemic? a review

Thomas, M. J., Lal, V., Baby, A. K., Rabeeh, V. M., James, A., & Raj, A. K. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103787 · Cited by 49 · see citing works

Pragmatic AI-augmentation in mental healthcare: Key technologies, potential benefits, and real-world challenges and solutions for frontline clinicians

Kellogg, K. C., & Sadeh‐Sharvit, S. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.990370 · Cited by 47 · see citing works

Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure

Swaroop, S., Buçinca, Z., Gajos, K. Z., & Doshi-Velez, F. (2024) · Proceedings of the 29th International Conference on Intelligent User Interfaces · doi:10.1145/3640543.3645206 · Cited by 49 · see citing works

Explainability for experts: A design framework for making algorithms supporting expert decisions more explainable

Simkute, A., Luger, E. A., Jones, B., Evans, M., & Jones, R. (2021) · Journal of Responsible Technology · doi:10.1016/j.jrt.2021.100017 · Cited by 40 · see citing works

Current applications of artificial intelligence in vascular surgery

Fischer, U. M., Shireman, P. K., & Lin, J. C. (2021) · Seminars in Vascular Surgery · doi:10.1053/j.semvascsurg.2021.10.008 · Cited by 39 · see citing works

Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments

Jacobsohn, G. C., Leaf, M. A., Liao, F., Maru, A., Engstrom, C. J., Salwei, M. E., Pankratz, G. T., Eastman, A., Carayon, P., Wiegmann, D. A., et al. (2021) · Healthcare · doi:10.1016/j.hjdsi.2021.100598 · Cited by 40 · see citing works

Generative adversarial U-Net for domain-free few-shot medical diagnosis

Chen, X., Li, Y., Yao, L., Adeli, E., Zhang, Y., & Wang, X. (2022) · Pattern Recognition Letters · doi:10.1016/j.patrec.2022.03.022 · Cited by 37 · see citing works

Challenges for augmenting intelligence in cardiac imaging

Sengupta, P. P., Dey, D., Davies, R. H., Duchateau, N., & Yanamala, N. V. K. (2024) · The Lancet Digital Health · doi:10.1016/s2589-7500(24)00142-0 · Cited by 38 · see citing works

A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data

Tutsoy, Ö., & Sümbül, H. E. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae344 · Cited by 33 · see citing works

Interpretable Optimization: Why and How We Should Explain Optimization Models

Lumbreras, S., & Ciller, P. (2025) · Applied Sciences · doi:10.3390/app15105732 · Cited by 29 · see citing works

Optimizing Clinical Decision Support System Functionality by Leveraging Specific Human-Computer Interaction Elements: Insights From a Systematic Review

Azadi, A., & García‐Peñalvo, F. J. (2025) · JMIR Human Factors · doi:10.2196/69333 · Cited by 33 · see citing works

Generative AI in Knowledge Work: Design Implications for Data Navigation and Decision-Making

Yun, B., Feng, D., Chen, A. S., Nikzad, A., & Salehi, N. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713337 · Cited by 28 · see citing works

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI

di Noia, C., Grist, J. T., Riemer, F., Lyasheva, M., Fabozzi, M., Castelli, M., Lodi, R., Tonon, C., Rundo, L., & Zaccagna, F. (2022) · Diagnostics · doi:10.3390/diagnostics12092125 · Cited by 23 · see citing works

A Cognitive Medical Decision Support System for IoT-Based Human-Computer Interface in Pervasive Computing Environment

Gou, H., Zhang, G., Medeiros, E. P., Jagatheesaperumal, S. K., & de Albuquerque, V. H. C. (2024) · Cognitive Computation · doi:10.1007/s12559-023-10242-4 · Cited by 22 · see citing works

A review on the efficacy of artificial intelligence for managing anxiety disorders

Das, K. P., & Gavade, P. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1435895 · Cited by 23 · see citing works

Personalising AI Assistance Based on Overreliance Rate in AI-Assisted Decision Making

Swaroop, S., Buçinca, Z., Gajos, K. Z., & Doshi-Velez, F. (2025) · Proceedings of the 30th International Conference on Intelligent User Interfaces · doi:10.1145/3708359.3712128 · Cited by 20 · see citing works

"When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology

Rosbach, E., Ammeling, J., Krügel, S., Kießig, A., Fritz, A., Ganz, J., Puget, C., Donovan, T., Klang, A., Köller, M. C., et al. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713319 · Cited by 18 · see citing works

Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person

Abidi, M. H. (2024) · Scientific Reports · doi:10.1038/s41598-024-82624-z · Cited by 20 · see citing works

A Systematic Review of Nurses' Perceptions of Electronic Health Record Usability Based on the Human Factor Goals of Satisfaction, Performance, and Safety

Park, S., Marquard, J. L., Austin, R. R., Pieczkiewicz, D. S., Jantraporn, R., & Delaney, C. W. (2024) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001084 · Cited by 18 · see citing works

Incorporating medical domain knowledge into data-driven method: A vessel attention guided multi-granularity network for automatic cataract classification

Xu, X., Zhao, L., Li, J., & Li, L. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122671 · Cited by 17 · see citing works

The Use of Tangible User Interfaces in K12 Education Settings: A Systematic Mapping Study

Gallud, J. A., Tesoriero, R., Lozano, M. D., Penichet, V. M. R., & Fardoun, H. M. (2022) · IEEE Access · doi:10.1109/access.2022.3154794 · Cited by 16 · see citing works

On Unsupervised Methods for Medical Image Segmentation: Investigating Classic Approaches in Breast Cancer DCE-MRI

Militello, C., Ranieri, A., Rundo, L., D’Angelo, I., Marinozzi, F., Bartolotta, T. V., Bini, F., & Russo, G. I. (2021) · Applied Sciences · doi:10.3390/app12010162 · Cited by 16 · see citing works

Socrates: Data Story Generation via Adaptive Machine-Guided Elicitation of User Feedback

Wu, G., Guo, S., Hoffswell, J., Chan, G. Y.-Y., Rossi, R. A., & Koh, E. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3327363 · Cited by 15 · see citing works

Diagnosing an overcrowded emergency department from its Electronic Health Records

Marzano, L., Darwich, A. S., Raghothama, J., Lethvall, S., Falk, N., Bodeby, P., & Meijer, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-60888-9 · Cited by 15 · see citing works

Enhancing Perceived Value in Human-Computer Interaction: The Mediating Role of User Participation and the Moderating Role of Task Complexity

Zheng, H., Xiao, D., & Zhou, J. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2350839 · Cited by 15 · see citing works

Data visualization in healthcare and medicine: a survey

Tan, X., Suo, X., Li, W., Bi, L., & Yao, F. (2024) · The Visual Computer · doi:10.1007/s00371-024-03586-x · Cited by 19 · see citing works

The human-AI relationship in decision-making: AI explanation to support people on justifying their decisionsPreprint

Ferreira, J. J., & Monteiro, M. D. S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.05460 · Cited by 15 · see citing works

Assessing Retrieval-Augmented Large Language Model Performance in Emergency Department ICD-10-CM Coding Compared to Human CodersPreprint

Klang, E., Tessler, I., Apakama, D. U., Abbott, E. E., Glicksberg, B. S., Arnold, M., Moses, A., Sakhuja, A., Soroush, A., Charney, A. W., et al. (2024) · medRxiv · doi:10.1101/2024.10.15.24315526 · Cited by 15 · see citing works

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Landolsi, M. Y., Hlaoua, L., & Romdhane, L. B. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15080-y · Cited by 14 · see citing works

Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities

Marquard, J. L. (2021) · Yearbook of Medical Informatics · doi:10.1055/s-0041-1726511 · Cited by 12 · see citing works

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Kirby, K., & Anwar, M. N. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e04982 · Cited by 16 · see citing works

Estimation of the Prostate Volume from Abdominal Ultrasound Images by Image-Patch Voting

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Rundo, L., Tangherloni, A., Cazzaniga, P., Mistri, M., Galimberti, S., Woitek, R., Sala, E., Mauri, G., & Nobile, M. S. (2021) · The Journal of Supercomputing · doi:10.1007/s11227-020-03565-8 · Cited by 11 · see citing works

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Contino, S., Cruciata, L., Gambino, O., & Pirrone, R. (2024) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2024.108113 · Cited by 10 · see citing works

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Rodrigues, A. M. M., de Almeida, T. D., Silva, L. A. B., & Costa, C. M. A. (2024) · IEEE Access · doi:10.1109/access.2024.3441469 · Cited by 10 · see citing works

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Mishra, R., Satpathy, R., & Pati, B. (2023) · EAI Endorsed Transactions on Pervasive Health and Technology · doi:10.4108/eetpht.9.4186 · Cited by 10 · see citing works

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He, X., Xi, Z., Ding, H., Liu, Y., & Zhu, H. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2235882 · Cited by 9 · see citing works

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Laraichi, O., Daim, T. U., Alzahrani, S., Hogaboam, L., Bolatan, G. İ. S., & Moughari, M. M. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102736 · Cited by 9 · see citing works

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Fanfani, M., Palesi, L. A. I., & Nesi, P. (2026) · Big Data and Cognitive Computing · doi:10.3390/bdcc10060186 · Cited by 9 · see citing works

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Bhattacharya, D., Eggert, D., Betz, C. S., & Schlaefer, A. (2022) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22795 · Cited by 9 · see citing works

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Holmlund, T. B., Chandler, C., Foltz, P. W., Diaz-Asper, C. M., Cohen, A. S., Rodriguez, Z. B., & Elvevåg, B. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.09.020 · Cited by 8 · see citing works

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Kang, C., Lee, C., Zhao, X., Lee, D., Shin, J., & Lee, J. (2024) · Travel Behaviour and Society · doi:10.1016/j.tbs.2024.100915 · Cited by 8 · see citing works

Human-Precision Medicine Interaction: Public Perceptions of Polygenic Risk Score for Genetic Health Prediction

Sun, Y., Tenesa, A., & Vines, J. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713567 · Cited by 8 · see citing works

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Militello, C., Rundo, L., Dimarco, M., Orlando, A. A. M., D’Angelo, I., Conti, V., & Bartolotta, T. V. (2022) · Applied Sciences · doi:10.3390/app12115512 · Cited by 8 · see citing works

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Fadja, A. N., Fraccaroli, M., Bizzarri, A., Mazzuchelli, G., & Lamma, E. (2022) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-022-02674-1 · Cited by 8 · see citing works

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Shams‐Vahdati, N., Vahdati, S. S., & Samad‐Soltani, T. (2024) · Health Science Reports · doi:10.1002/hsr2.1931 · Cited by 7 · see citing works

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Rundo, L., Militello, C., Conti, V., Zaccagna, F., & Han, C. (2021) · Journal of Imaging · doi:10.3390/jimaging7110237 · Cited by 7 · see citing works

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Collado-Montañez, J., Valdivia, M. T. M., & Martínez‐Cámara, E. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112745 · Cited by 6 · see citing works

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Sosa, P., Kharrazi, H. H. K., & Lehmann, H. P. (2025) · Public Health · doi:10.1016/j.puhe.2024.12.053 · Cited by 6 · see citing works

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Curiello, S., Iannuzzi, E., Meissner, D., & Nigro, C. (2025) · European Journal of Innovation Management · doi:10.1108/ejim-01-2024-0078 · Cited by 7 · see citing works

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Faso, E. A. L., Gambino, O., & Pirrone, R. (2021) · Applied Sciences · doi:10.3390/app11062721 · Cited by 6 · see citing works

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Andersson, S. W., Richardson, M. X., Stridsberg, S. L., Ryan, J. C., Sukums, F. K., & Goh, Y. S. (2022) · JMIR Research Protocols · doi:10.2196/40565 · Cited by 6 · see citing works

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Giler-Velásquez, G., Marcillo-Delgado, B., Vaca-Cárdenas, M. E., & Vaca-Cárdenas, L. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-90241-4_12 · Cited by 6 · see citing works

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Alnasser, A. A. A. A. N., Hassanain, M. A., Alnasser, M. A., & Alnasser, A. H. A. (2024) · Journal of Health Organization and Management · doi:10.1108/jhom-04-2024-0135 · Cited by 5 · see citing works

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Jamali, S. N., Admodisastro, N. I., Kamaruddin, A., & Hassan, S. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0141186 · Cited by 4 · see citing works

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Sharaf, D. E., Shebel, H. M., El-Diasty, T. A., Osman, Y., Khater, S. M., Abdelhamid, M., & Atta, H. M. A. E. (2022) · Clinical Radiology · doi:10.1016/j.crad.2022.05.024 · Cited by 3 · see citing works

Hyper-parameter Optimization of LSTM Network Using Genetic Algorithm and Q-Learning Algorithm for Classification of COVID-19 Dataset

Parvizimosaed, M., Esnaashari, M., Damia, A., & Paband, M. T. (2023) · International Conference on Web Research (ICWR) · doi:10.1109/icwr57742.2023.10139161 · Cited by 3 · see citing works

Time Is Money: Considerations for Measuring the Radiological Reading Time

Sexauer, R., & Bestler, C. (2022) · Journal of Imaging · doi:10.3390/jimaging8080208 · Cited by 2 · see citing works

Recent Developments in Workflow Research in Healthcare

Ozkaynak, M., Shan, Z., & Wu, D. T. Y. (2025) · Cognitive informatics in biomedicine and healthcare · doi:10.1007/978-3-031-82971-0_6 · Cited by 2 · see citing works

Assessing oral surgery residents’ competencies and training needs in tomography interfaces through a usability framework

Dogan, Y., & Şirin, Y. (2025) · BMC Medical Education · doi:10.1186/s12909-025-07673-y · Cited by 3 · see citing works

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Sheela, S. V., Abhinand, P., & Radhika, K. R. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-99891-8.00007-3 · Cited by 2 · see citing works

The applications of artificial intelligence in the healthcare industry

Wu, Y. (2024) · Applied and Computational Engineering · doi:10.54254/2755-2721/75/20240534 · Cited by 2 · see citing works

The user-centered design and development of a childhood and adolescent obesity Electronic Health Record tool, a mixed-methods study

Bosworth, K. T., Ghosh, P., Flowers, L., Proffitt, R. M., Koopman, R. J., Tosh, A. K., Wilson, G., & Braddock, A. S. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1396085 · Cited by 3 · see citing works

Towards accurate and automatic emergency department workflow characterization using a real-time locating system

Wagner, M., Queck, A., Beekers, P., Tolhuizen, L. M. G. M., Synnatschke, A., Boesing, J., & Chatterjea, S. (2023) · International Journal of Healthcare Management · doi:10.1080/20479700.2023.2172829 · Cited by 2 · see citing works

PC-LSTM: Ontology-based Long Short-Term Memory State Model for Data Incompleteness Prediction

Shelleh, M., & Gurupur, V. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/embc48229.2022.9871867 · Cited by 1 · see citing works

Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation

Ye, A., Chen, Q. Z., & Zhang, A. X. (2023) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v11i1.27559 · Cited by 1 · see citing works

Prioritizing human-centered cancer care in a digital era

Smith, G., Bergerot, C. D., Epstein, A. S., Nelson, J. E., Salins, N., Vasudeva Bhat, K., Lewis, S. C., Skelton, J. M., Parikh, R. B., Bhoo-Pathy, N., et al. (2025) · EClinicalMedicine · doi:10.1016/j.eclinm.2025.103695 · Cited by 1 · see citing works

Smart Ward Control Based on a Wearable Multimodal Brain–Computer Interface Mouse

Zhu, J., Li, K., Chen, S., Huang, H., Zhang, Y., Hu, L., & Li, Y. (2026) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2026.3653138 · Cited by 1 · see citing works

Revealing the Physician’s Task Conceptualization in Melanoma Treatment: Qualitative User Experience Study

Hartmann, E. M., Küper, A., Swoboda, J., Beckmann, C. L., Lodde, G. C., Livingstone, E., Schadendorf, D., & Sachweh, S. (2026) · JMIR Cancer · doi:10.2196/79294 · Cited by 1 · see citing works

HCI for biomedical decision-making: From diagnosis to therapy

Gambino, O., Rundo, L., Pirrone, R., & Vitabile, S. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103593 · Cited by 1 · see citing works

Health personalisation

Berkovsky, S., & Coiera, E. W. (2021) · ACM SIGWEB Newsletter · doi:10.1145/3473044.3473048

Advanced Computational Methods for Oncological Image Analysis

Rundo, L., Militello, C., Conti, V., Zaccagna, F., & Han, C. (2021) · MDPI eBooks · doi:10.3390/books978-3-0365-2555-6

A Hierarchical Decision Model to Evaluate Healthcare Organization's Readiness to Implement Clinical Decision Support Systems

Laraichi, O. (2023) · doi:10.15760/etd.3562

Research on structuring of pediatric electronic medical records based on joint extraction using BART

Li, Y., Wu, P., Zhang, K., Li, J., Liu, X., Zhang, H., & Min, J. (2024) · International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT) · doi:10.1117/12.3031049

Intelligent Reconstruction and Effectiveness Evaluation of Nursing Workflow for Future Hospitals

Su, M., & Wang, D. (2024) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2024-3248

Health Informatics Systems for Information and Decisional Control in Cancer Patients' Medical Decision-Making

Panda, S. S., Mane, M., & Singh, S. K. (2023) · Seminars in Medical Writing and Education · doi:10.56294/mw2023129

Significance of computational intelligence and genetic programming based models for real-time disease monitoring in wireless sensor networks

Ramírez, C. E. M., Chari, T. A., & Shoko, R. (2025) · Cogent Engineering · doi:10.1080/23311916.2025.2605950

Designing Explainable AI to Improve Human-AI Team Performance: A Medical Stakeholder-Driven Scoping ReviewPreprint

Shank, D. B., Canfield, C., & Subramanian, H. V. (2024) · OSF Preprints (OSF Preprints)

Ontology-Based Medication Named Entity Recognition Using Pretrained Transformer Models From a Thai Hospital: Model Fine-Tuning and Validation Study

Isaradech, N., Sirikul, W., Schulz, S., & Kreuzthaler, M. (2026) · JMIR Formative Research · doi:10.2196/82685

Designing Effective Clinical Tools for Measuring Navigation Deficits Associated with Cognitive Impairment

Schinazi, V. R., Colombo, G., & Minta, K. (2026) · Springer eBooks · doi:10.1007/978-3-032-20563-6_15

Human-Computer Interaction and Healthcare

Mohanty, A. (2024) · CRC Press eBooks · doi:10.1201/9781032624891-1

HCI for biomedical decision-making: From diagnosis to therapy

Gambino, O., Rundo, L., Pirrone, R., & Vitabile, S. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103593 · Cited by 1 · see citing works

Artificial intelligence and computer-aided diagnosis in diagnostic decisions: 5 questions for medical informatics and human-computer interface research

Brunyé, T. T., Mitroff, S. R., & Elmore, J. G. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf123 · Cited by 22 · see citing works

Human–Computer Interaction for Medicine and Health Care (HCI4MED): Towards making Information usable

(2013)

Applications and Challenges of Human Computer Interaction and AI Interfaces for Health Care

Hutch, M. R., & Luo, Y. (2024) · Cognitive informatics in biomedicine and healthcare · doi:10.1007/978-3-031-69947-4_4 · Cited by 7 · see citing works