Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril

Smart wearable devices in cardiovascular care: Where we are and how to move forward

Bayoumy, K., Gaber, M., Elshafeey, A., Mhaimeed, O., Dineen, E. H., Marvel, F. A., Martin, S. S., Muse, E. D., Turakhia, M. P., Tarakji, K. G., et al. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00522-7 · Cited by 829 · see citing works

Artificial intelligence for good health: a scoping review of the ethics literature.

Murphy, K., Di Ruggiero, E., Upshur, R., Willison, D. J., Malhotra, N., Cai, J. C., Malhotra, N., Lui, V., & Gibson, J. (2021) · BMC Medical Ethics · doi:10.1186/s12910-021-00577-8 · Cited by 435 · see citing works

Identifying Ethical Considerations for Machine Learning Healthcare Applications

Char, D. S., Abràmoff, M. D., & Feudtner, C. (2020) · The American Journal of Bioethics · doi:10.1080/15265161.2020.1819469 · Cited by 415 · see citing works

Artificial intelligence in medical education: a cross-sectional needs assessment

Civaner, M. M., Uncu, Y., Bulut, F., Chalil, E. G., & Tatli, A. (2022) · BMC Medical Education · doi:10.1186/s12909-022-03852-3 · Cited by 363 · see citing works

Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals

Russell, R. G., Lovett Novak, L., Patel, M., Garvey, K. V., Craig, K. J. T., Jackson, G. P., Moore, D., & Miller, B. M. (2023) · Academic Medicine · doi:10.1097/acm.0000000000004963 · Cited by 320 · see citing works

Global regulatory frameworks for the use of Artificial Intelligence (AI) in the healthcare services sector

Palaniappan, K., Lin, E. Y. T., & Vogel, S. (2024) · Healthcare · doi:10.3390/healthcare12050562 · Cited by 301 · see citing works

Human-Centered Design to Address Biases in Artificial Intelligence

Chen, Y., Clayton, E. W., Novak, L. L., Anders, S. H., & Malin, B. (2023) · Journal of Medical Internet Research · doi:10.2196/43251 · Cited by 211 · see citing works

Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence

Bonkhoff, A. K., & Grefkes, C. (2021) · Brain · doi:10.1093/brain/awab439 · Cited by 208 · see citing works

Exploring stakeholder attitudes towards AI in clinical practice

Scott, I. A., Carter, S. M., & Coiera, E. (2021) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2021-100450 · Cited by 193 · see citing works

AI, Health, and Health Care Today and Tomorrow: The JAMA Summit Report on Artificial Intelligence

Angus, D. C., Khera, R., Lieu, T., Liu, V., Ahmad, F. S., Anderson, B., Bhavani, S. V., Bindman, A., Brennan, T., Celi, L. A., et al. (2025) · JAMA · doi:10.1001/jama.2025.18490 · Cited by 195 · see citing works

Priorities for successful use of artificial intelligence by public health organizations: a literature review

Fisher, S., & Rosella, L. C. (2022) · BMC Public Health · doi:10.1186/s12889-022-14422-z · Cited by 190 · see citing works

Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity

Alami, H., Lehoux, P., Auclair, Y., de Guise, M., Gagnon, M., Shaw, J., Roy, D. A., Fleet, R. P., Ahmed, M. A. A., & Fortin, J. (2020) · Journal of Medical Internet Research · doi:10.2196/17707 · Cited by 180 · see citing works

Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review

(2023) · doi:10.2196/40337 · Cited by 156 · see citing works

Clinician checklist for assessing suitability of machine learning applications in healthcare

Scott, I. A., Carter, S. M., & Coiera, E. W. (2021) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2020-100251 · Cited by 140 · see citing works

Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks

Crossnohere, N. L., Elsaid, M. I., Paskett, J., Bose‐Brill, S., & Bridges, J. F. P. (2022) · Journal of Medical Internet Research · doi:10.2196/36823 · Cited by 131 · see citing works

Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study

Shevtsova, D., Ahmed, A., Boot, I. W. A., Sanges, C., Hudecek, M., Jacobs, J. J. L., Hort, S., & Vrijhoef, H. J. M. (2024) · JMIR Human Factors · doi:10.2196/47031 · Cited by 124 · see citing works

A sociotechnical systems framework for the application of artificial intelligence in health care delivery

Salwei, M. E., & Carayon, P. (2022) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/15553434221097357 · Cited by 112 · see citing works

Regulating AI in Mental Health: Ethics of Care Perspective

Tavory, T. (2024) · JMIR Mental Health · doi:10.2196/58493 · Cited by 108 · see citing works

Advancing AI in healthcare: A comprehensive review of best practices

Polevikov, S. (2023) · Clinica Chimica Acta · doi:10.1016/j.cca.2023.117519 · Cited by 112 · see citing works

Simulation-based approaches for drug delivery systems: Navigating advancements, opportunities, and challenges

Salahshoori, I., Golriz, M., Nobre, M. A. L., Mahdavi, S., Malekshah, R. E., Javdani-Mallak, A., Jorabchi, M. N., Khonakdar, H. A., Wang, Q., Mohammadi, A. H., et al. (2023) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2023.123888 · Cited by 106 · see citing works

Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

Antes, A. L., Burrous, S., Sisk, B. A., Schuelke, M. J., Keune, J. D., & DuBois, J. M. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01586-8 · Cited by 105 · see citing works

How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices

Lyell, D., Coiera, E., Chen, J., Shah, P., & Magrabi, F. (2021) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2020-100301 · Cited by 95 · see citing works

Emerging Technologies for Next Generation Remote Health Care and Assisted Living

Ahmad, I., Asghar, Z., Kumar, T., Li, G., Manzoor, A., Mikhaylov, K., Shah, S. A., Höyhtyä, M., Reponen, J., Huusko, J., et al. (2022) · IEEE Access · doi:10.1109/access.2022.3177278 · Cited by 101 · see citing works

Automated Detection of Major Depressive Disorder With EEG Signals: A Time Series Classification Using Deep Learning

Rafiei, A., Zahedifar, R., Sitaula, C., & Marzbanrad, F. (2022) · IEEE Access · doi:10.1109/access.2022.3190502 · Cited by 88 · see citing works

Applications of artificial intelligence for nursing: has a new era arrived?

Bulck, L. V., Couturier, R., & Moons, P. (2022) · European Journal of Cardiovascular Nursing · doi:10.1093/eurjcn/zvac097 · Cited by 73 · see citing works

Artificial Intelligence: Exploring the Future of Innovation in Allergy Immunology

MacMath, D., Chen, M., & Khoury, P. (2023) · Current Allergy and Asthma Reports · doi:10.1007/s11882-023-01084-z · Cited by 66 · see citing works

Artificial intelligence in clinical research of cancers

Shao, D., Dai, Y., Li, N., Cao, X., Zhao, W., Li, C., Rong, Z., Huang, L., Wang, Y., & Zhao, J. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab523 · Cited by 64 · see citing works

Artificial intelligence in thoracic surgery: past, present, perspective and limits

Etienne, H., Hamdi, S., Le Roux, M., Camuset, J., Khalife-Hocquemiller, T., Giol, M., Debrosse, D., & Assouad, J. (2020) · European Respiratory Review · doi:10.1183/16000617.0010-2020 · Cited by 48 · see citing works

Advancing the Understanding of the Role of Responsible AI in the Continued Use of IoMT in Healthcare

Al-Dhaen, F., Hou, J., Rana, N. P., & Weerakkody, V. (2021) · Information Systems Frontiers · doi:10.1007/s10796-021-10193-x · Cited by 58 · see citing works

Expectations for Artificial Intelligence (AI) in Psychiatry

Monteith, S., Glenn, T., Geddes, J. R., Whybrow, P. C., Achtyes, E. D., & Bauer, M. (2022) · Current Psychiatry Reports · doi:10.1007/s11920-022-01378-5 · Cited by 56 · see citing works

Artificial Intelligence In Health And Health Care: Priorities For Action

Matheny, M. E., Goldsack, J. C., Saria, S., Shah, N. H., Gerhart, J. L., Cohen, I. G., Price, W. N., Patel, B., Payne, P., Embí, P. J., et al. (2025) · Health Affairs · doi:10.1377/hlthaff.2024.01003 · Cited by 69 · see citing works

Modeling Conceptual Framework for Implementing Barriers of AI in Public Healthcare for Improving Operational Excellence: Experiences from Developing Countries

Joshi, S., Sharma, M., Das, R. P., Rosak-Szyrocka, J., Żywiołek, J., Muduli, K., & Prasad, M. (2022) · Sustainability · doi:10.3390/su141811698 · Cited by 55 · see citing works

Artificial intelligence and machine learning for hemorrhagic trauma care

Peng, H. T., Siddiqui, M. M., Rhind, S. G., Zhang, J., da Luz, L. T., & Beckett, A. (2023) · Military Medical Research · doi:10.1186/s40779-023-00444-0 · Cited by 53 · see citing works

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record

Corbin, C. K., Maclay, R., Acharya, A., Mony, S., Punnathanam, S., Thapa, R., Kotecha, N., Shah, N. H., & Chen, J. H. (2023) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad114 · Cited by 59 · see citing works

From Code to Bedside: Implementing Artificial Intelligence Using Quality Improvement Methods

Smith, M., Sattler, A., Hong, G., & Lin, S. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06394-w · Cited by 51 · see citing works

Artificial intelligence (AI) acceptance in primary care during the coronavirus pandemic: What is the role of patients' gender, age and health awareness? A two-phase pilot study

Gal, H. C. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2022.931225 · Cited by 56 · see citing works

Exploiting the power of information in medical education

Cutrer, W. B., Spickard, W. A., Triola, M. M., Allen, B. L., Spell, N. O., Herrine, S. K., Dalrymple, J. L., Gorman, P., & Lomis, K. D. (2021) · Medical Teacher · doi:10.1080/0142159x.2021.1925234 · Cited by 49 · see citing works

Internet of Medical Things (IoMT): Applications, Challenges, and Prospects in a Data-Driven Technology

Ajagbe, S. A., Awotunde, J. B., Adesina, A. O., Achimugu, P., & Kumar, T. A. (2022) · Springer eBooks · doi:10.1007/978-981-16-8150-9_14 · Cited by 49 · see citing works

Preparing Clinicians for a Clinical World Influenced by Artificial Intelligence

James, C. A., Wachter, R. M., & Woolliscroft, J. O. (2022) · JAMA · doi:10.1001/jama.2022.3580 · Cited by 48 · see citing works

Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives

Fazakarley, C.-A., Breen, M. A., Leeson, P., Thompson, B. T., & Williamson, V. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-076950 · Cited by 53 · see citing works

Ethical considerations in design and implementation of home-based smart care for dementia

Hine, C., Nilforooshan, R., & Barnaghi, P. M. (2022) · Nursing Ethics · doi:10.1177/09697330211062980 · Cited by 48 · see citing works

Sustainable deployment of clinical prediction tools—a 360° approach to model maintenance

Davis, S. E., Embí, P. J., & Matheny, M. E. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae036 · Cited by 46 · see citing works

Consequence of Resistance to Change on AI Readiness: Mediating–Moderating Role of Task-oriented Leadership and High-Performance Work System in the Hospitality Sector

Li, C., Ashraf, S. F., Amin, S., & Safdar, M. N. (2023) · SAGE Open · doi:10.1177/21582440231217731 · Cited by 55 · see citing works

Development Issues of Healthcare Robots: Compassionate Communication for Older Adults with Dementia

Tanioka, T., Yokotani, T., Tanioka, R., Betriana, F., Matsumoto, K., Locsin, R. C., Zhao, Y., Osaka, K., Miyagawa, M., & Schoenhofer, S. O. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18094538 · Cited by 43 · see citing works

How Artificial Intelligence is altering the nursing workforce

Yakusheva, O., Bouvier, M. J., & Hagopian, C. O. P. (2024) · Nursing Outlook · doi:10.1016/j.outlook.2024.102300 · Cited by 46 · see citing works

Demystifying machine learning: a primer for physicians

Scott, I. A. (2021) · Internal Medicine Journal · doi:10.1111/imj.15200 · Cited by 43 · see citing works

Implementing quality management systems to close the AI translation gap and facilitate safe, ethical, and effective health AI solutions

Overgaard, S. M., Graham, M. G., Brereton, T., Pencina, M. J., Halamka, J. D., Vidal, D. E., & Economou-Zavlanos, N. J. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00968-8 · Cited by 43 · see citing works

Emerging algorithmic bias: fairness drift as the next dimension of model maintenance and sustainability

Davis, S. E., Dorn, C., Park, D. J., & Matheny, M. E. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf039 · Cited by 43 · see citing works

Physician’s autonomy in the face of AI support: walking the ethical tightrope

Funer, F., & Wiesing, U. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1324963 · Cited by 39 · see citing works

Artificial Intelligence in Medicine: Text Mining of Health Care Workers’ Opinions

Nitiéma, P. (2022) · Journal of Medical Internet Research · doi:10.2196/41138 · Cited by 34 · see citing works

Open questions and research gaps for monitoring and updating AI-enabled tools in clinical settings

Davis, S. E., Walsh, C. G., & Matheny, M. E. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.958284 · Cited by 33 · see citing works

Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study

Siglen, E., Vetti, H. H., Augestad, M., Steen, V. M., Lunde, Å., & Bjorvatn, C. (2023) · Journal of Medical Internet Research · doi:10.2196/46571 · Cited by 33 · see citing works

Availability of Evidence for Predictive Machine Learning Algorithms in Primary Care

Rakers, M. M., van Buchem, M. M., Kucenko, S., de Hond, A., Kant, I. M. J., van Smeden, M., Moons, K. G. M., Leeuwenberg, A., Chavannes, N. H., Villalobos-Quesada, M. J., et al. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.32990 · Cited by 36 · see citing works

Medical Information Mart for Intensive Care: A Foundation for the Fusion of Artificial Intelligence and Real-World Data

Rogers, P. B., Wang, D., & Lu, Z. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.691626 · Cited by 33 · see citing works

Data Interoperability and Harmonization in Cardiovascular Genomic and Precision Medicine

Chahal, C. A. A., Alahdab, F., Asatryan, B., Addison, D., Aung, N., Chung, M. K., Denaxas, S., Dunn, J., Hall, J. L., Pamir, N., et al. (2025) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.124.004624 · Cited by 35 · see citing works

Epistemic Rights and Responsibilities of Digital Simulacra for Biomedicine

Cho, M. K., & Martinez‐Martin, N. (2022) · The American Journal of Bioethics · doi:10.1080/15265161.2022.2146785 · Cited by 30 · see citing works

Aligning quality improvement efforts and policy goals in a national integrated health system

Braganza, M. Z., Pearson, E., Avila, C. J., Zlowe, D., Øvretveit, J., & Kilbourne, A. M. (2022) · Health Services Research · doi:10.1111/1475-6773.13944 · Cited by 30 · see citing works

External Validation of the eRADAR Risk Score for Detecting Undiagnosed Dementia in Two Real-World Healthcare Systems

Coley, R. Y., Smith, J. J., Karliner, L., Idu, A., Lee, S. J., Fuller, S., Lam, R., Barnes, D. E., & Dublin, S. (2022) · Journal of General Internal Medicine · doi:10.1007/s11606-022-07736-6 · Cited by 26 · see citing works

Risky business: a scoping review for communicating results of predictive models between providers and patients

Walsh, C. G., McKillop, M. M., Lee, P., Harris, J. W., Simpson, C., & Novak, L. L. (2021) · JAMIA Open · doi:10.1093/jamiaopen/ooab092 · Cited by 26 · see citing works

Ethics dumping in artificial intelligence

Bélisle-Pipon, J.-C., & Victor, G. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1426761 · Cited by 26 · see citing works

AI Quality Standards in Health Care: Rapid Umbrella Review

Kuziemsky, C. E., Chrimes, D., Minshall, S. R., Mannerow, M., & Lau, F. (2024) · Journal of Medical Internet Research · doi:10.2196/54705 · Cited by 28 · see citing works

Qualitative ethical technology assessment of artificial intelligence (AI) and the internet of things (IoT) among filipino Gen Z members: implications for ethics education in higher learning institutions

Jabar, M. A., Chiong-Javier, E., & Sherer, P. P. (2024) · Asia Pacific Journal of Education · doi:10.1080/02188791.2024.2303048 · Cited by 27 · see citing works

Application of Virtual Reality, Artificial Intelligence, and Other Innovative Technologies in Healthcare Education (Nursing and Midwifery Specialties): Challenges and Strategies

Georgieva-Tsaneva, G., Serbezova, I., & Beloeva, S. (2024) · Education Sciences · doi:10.3390/educsci15010011 · Cited by 25 · see citing works

Explainable AI (XAI) Applied in Machine Learning for Pain Modeling: A Review

Madanu, R., Abbod, M., Hsiao, F., Chen, W., & Shieh, J.-S. (2022) · Technologies · doi:10.3390/technologies10030074 · Cited by 27 · see citing works

Increasing use of artificial intelligence in genomic medicine for cancer care- the promise and potential pitfalls

O’Connor, O., & McVeigh, T. P. (2025) · BJC Reports · doi:10.1038/s44276-025-00135-4 · Cited by 23 · see citing works

The future of artificial intelligence in thoracic surgery for non-small cell lung cancer treatment a narrative review

Abbaker, N., Minervini, F., Guttadauro, A., Solli, P., Cioffi, U., & Scarci, M. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1347464 · Cited by 22 · see citing works

Leveraging law and ethics to promote safe and reliable AI/ML in healthcare

Drabiak, K. (2022) · Frontiers in Nuclear Medicine · doi:10.3389/fnume.2022.983340 · Cited by 22 · see citing works

A framework to identify ethical concerns with ML-guided care workflows: a case study of mortality prediction to guide advance care planning

Cagliero, D., Deuitch, N. T., Shah, N. H., Feudtner, C., & Char, D. S. (2023) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad022 · Cited by 23 · see citing works

Ten principles for data sharing and commercialization

Cole, C. L., Sengupta, S., Rossetti, S. C., Vawdrey, D. K., Halaas, M., Maddox, T. M., Gordon, G. D., Dave, T., Payne, P., Williams, A. E., et al. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa260 · Cited by 23 · see citing works

Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes

Shapiro, M. R., Tallon, E. M., Brown, M. E., Posgai, A. L., Clements, M. A., & Brusko, T. M. (2024) · Diabetologia · doi:10.1007/s00125-024-06339-6 · Cited by 19 · see citing works

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

Morris, A. H., Horvat, C. M., Stagg, B. C., Grainger, D. W., Lanspa, M. J., Orme, J. F., Clemmer, T. P., Weaver, L. K., Thomas, F. O., Grissom, C. K., et al. (2022) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocac143 · Cited by 20 · see citing works

Engaging Multidisciplinary clinical users in the design of an artificial intelligence-powered graphical user interface for intensive care unit instability decision support

Helman, S., Terry, M. A., Pellathy, T., Hravnak, M., George, E., Al-Zaiti, S., & Clermont, G. (2023) · Applied Clinical Informatics · doi:10.1055/s-0043-1775565 · Cited by 20 · see citing works

Artificial intelligence in pediatrics: the future is now

Knake, L. A. (2022) · Pediatric Research · doi:10.1038/s41390-022-01972-6 · Cited by 20 · see citing works

Harnessing artificial intelligence for enhanced veterinary diagnostics: A look to quality assurance, Part I Model development

Pacholec, C., Flatland, B., Xie, H., & Zimmerman, K. (2024) · Veterinary Clinical Pathology · doi:10.1111/vcp.13401 · Cited by 19 · see citing works

The Impact of Artificial Intelligence on Allergy Diagnosis and Treatment

Khan, M., Banerjee, S., Muskawad, S., Maity, R., Chowdhury, S. R., Ejaz, R., Kuuzie, E., & Satnarine, T. (2024) · Current Allergy and Asthma Reports · doi:10.1007/s11882-024-01152-y · Cited by 19 · see citing works

Forecasting the future of smart hospitals: findings from a real-time delphi study

Jovy-Klein, F., Stead, S., Salge, T. O., Sander, J., Diehl, A., & Antons, D. (2024) · BMC Health Services Research · doi:10.1186/s12913-024-11895-z · Cited by 25 · see citing works

AI-based medical ethics education: examining the potential of large language models as a tool for virtue cultivation

Okamoto, S., Kataoka, M., Itano, M., & Sawai, T. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06801-y · Cited by 18 · see citing works

Normativity and AI moral agency

Zafar, M. (2024) · AI and Ethics · doi:10.1007/s43681-024-00566-8 · Cited by 17 · see citing works

Ethical Challenges of Artificial Intelligence in Health Care: A Narrative Review

Hui, A. T., Ahn, S. S., Lye, C. T., & Deng, J. (2021) · Ethics in Biology Engineering and Medicine An International Journal · doi:10.1615/ethicsbiologyengmed.2022041580 · Cited by 19 · see citing works

Machine Learning and the Pursuit of High-Value Health Care

Ganguli, I., Gordon, W. J., Lupo, C., Sands-Lincoln, M., George, J., Jackson, G. P., Rhee, K. B. L., & Bates, D. W. (2020) · NEJM Catalyst · doi:10.1056/cat.20.0094 · Cited by 17 · see citing works

Perception of Medical Undergraduates on Artificial Intelligence in Medical Education: Qualitative Exploration

Seneviratne, T., Kodikara, K. G., Abeykoon, I., & Palpola, W. (2025) · JMIR Medical Education · doi:10.2196/73798 · Cited by 24 · see citing works

The Future of Thyroid Nodule Risk Stratification

Burgos, N., Ospina, N. S., & Sipos, J. A. (2022) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2021.12.002 · Cited by 16 · see citing works

Restoring Trust: The Need for Precision Medicine in Infectious Diseases, Public Health and Vaccines

Equils, O., Bakaj, A., Wilson-Mifsud, B., & Chatterjee, A. (2023) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2023.2234787 · Cited by 15 · see citing works

Prediction of Important Factors for Bleeding in Liver Cirrhosis Disease Using Ensemble Data Mining Approach

Aleksić, A., Nedeljković, S., Jovanović, M., Ranđelović, M., Vuković, M., Stojanović, V. S., Radovanović, R., Ranđelović, M., & Ranđelović, D. M. (2020) · Mathematics · doi:10.3390/math8111887 · Cited by 16 · see citing works

Bridging Artificial Intelligence and Medical Education: Navigating the Alignment Paradox

Turner, L., Knopp, M. I., Mendonça, E. A., & Desai, S. V. (2025) · ATS Scholar · doi:10.34197/ats-scholar.2024-0086ps · Cited by 15 · see citing works

Artificial intelligence in telemetry: what clinicians should know

Maslove, D. M., Elbers, P., & Clermont, G. (2021) · Intensive Care Medicine · doi:10.1007/s00134-020-06295-w · Cited by 15 · see citing works

A strategic approach to improving pharmacy enterprise automation: Development and initial application of the Autonomous Pharmacy Framework

Flynn, A. J., Fortier, C. R., Maehlen, H., Pierzinski, V., Runnebaum, R., Sullivan, M., Wagner, J., & Stevenson, J. G. (2021) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxab001 · Cited by 14 · see citing works

Informing the ethical review of human subjects research utilizing artificial intelligence

Makridis, C. A., Boese, A., Fricks, R., Workman, D. E., Klote, M., Mueller, J. M., Hildebrandt, I. J., Kim, M. P., & Alterovitz, G. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2023.1235226 · Cited by 16 · see citing works

Artificial Intelligence’s Contribution To Mental Health Education

Anand, N., Pant, L. M., Alam, T., Pundir, S., Thomas, L., & Rakshith, U. R. (2023) · International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) · doi:10.1109/icscds56580.2023.10104905 · Cited by 13 · see citing works

Development of a practical training method for a healthcare artificial intelligence (AI) chatbot

Lin, J., Joseph, T., Parga-Belinkie, J. J., Mandel, A., Schumacher, R., Neumann, K., Scalise, L., Gaulton, J., Christ, L., Leitner, K., et al. (2021) · BMJ Innovations · doi:10.1136/bmjinnov-2020-000530 · Cited by 13 · see citing works

Role of Artificial Intelligence in Multinomial Decisions and Preventative Nutrition in Alzheimer's Disease

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