Health Big Data Analytics: A Technology Survey

Deep learning in neural networks: an overview

Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works

MapReduce: simplified data processing on large clusters

Dean, J., & Ghemawat, S. (2008) · Communications of the ACM · doi:10.1145/1327452.1327492 · Cited by 18,476 · see citing works

Algorithm AS 136: A K-Means Clustering Algorithm

Hartigan, J. A., & Wong, M. A. (1979) · Applied Statistics · doi:10.2307/2346830 · Cited by 14,523 · see citing works

The sequence of the human genome

Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) · Science · doi:10.1126/science.1058040 · Cited by 13,909 · see citing works

Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

Sørlie, T., Perou, C., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., Hastie, T., Eisen, M., van de Rijn, M., Jeffrey, S., et al. (2001) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.191367098 · Cited by 11,695 · see citing works

Gene selection for cancer classification using support vector machines

Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954 · see citing works

Ensemble methods in machine learning

Dietterich, T. G. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45014-9_1 · Cited by 8,408 · see citing works

Support vector machines

Hearst, M. A., Dumais, S. T., Osuna, E., Platt, J., & Scholkopf, B. (1998) · IEEE Intelligent Systems and their Applications · doi:10.1109/5254.708428 · Cited by 7,243 · see citing works

Social Network Analysis

(2017) · Sage eBooks · doi:10.4135/9781483381411.n575 · Cited by 6,067 · see citing works

An efficient k-means clustering algorithm: analysis and implementation

Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, A. Y. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017616 · Cited by 5,660 · see citing works

The global k-means clustering algorithm

Likas, A. C., Vlassis, N. A., & Verbeek, J. J. (2002) · Pattern Recognition · doi:10.1016/s0031-3203(02)00060-2 · Cited by 3,755 · see citing works

Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing

Zaharia, M., Chowdhury, M., Das, T., Dave, A., Ma, J. H., McCauley, M., Franklin, M. J. M., Shenker, S. J., & Stoica, I. G. (2012) · Cited by 3,622 · see citing works

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

Kamnitsas, K., Ledig, C., Newcombe, V. F. J., Simpson, J. P., Kane, A. D., Menon, D. K., Rueckert, D., & Glocker, B. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.10.004 · Cited by 3,498 · cited 1× · see citing works

Untitled work

(2015) · Cited by 3,471 · see citing works

Machine Learning Applications in Cancer Prognosis and Prediction

Kourou, K., Exarchos, T. P., Exarchos, K. P., Karamouzis, M. V., & Fotiadis, D. I. (2015) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2014.11.005 · Cited by 3,338 · see citing works

Big data analytics in healthcare: promise and potential

Raghupathi, W., & Raghupathi, V. (2014) · Health Information Science and Systems · doi:10.1186/2047-2501-2-3 · Cited by 3,034 · see citing works

Ensemble based systems in decision making

Robi Polikar, A. (2006) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2006.1688199 · Cited by 2,960 · see citing works

Popular Ensemble Methods: An Empirical Study

Opitz, D., & Maclin, R. (1999) · Journal of Artificial Intelligence Research · doi:10.1613/jair.614 · Cited by 2,953 · see citing works

Diagnosis of multiple cancer types by shrunken centroids of gene expression

Tibshirani, R. J., Hastie, T. J., Narasimhan, B., & Chu, G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082099299 · Cited by 2,938 · see citing works

A fuzzy K-nearest neighbor algorithm

Keller, J. M., Gray, M. R., & Givens, J. A. (1985) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/tsmc.1985.6313426 · Cited by 2,686 · see citing works

Ensemble Methods: Foundations and Algorithms

Zhou, Z.-H. (2012) · doi:10.1201/b12207 · Cited by 2,534 · see citing works

MedRec: Using Blockchain for Medical Data Access and Permission Management

Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016) · 2016 2nd International Conference on Open and Big Data (OBD) · doi:10.1109/obd.2016.11 · Cited by 2,526 · see citing works

Apache Spark

Zaharia, M., Xin, R., Wendell, P., Das, T., Armbrust, M., Dave, A., Meng, X., Rosen, J., Venkataraman, S., Franklin, M. J. M., et al. (2016) · Communications of the ACM · doi:10.1145/2934664 · Cited by 2,443 · see citing works

Markov Models in Medical Decision Making: A Practical Guide

Sonnenberg, F. A., & Beck, J. R. (1993) · Medical Decision Making · doi:10.1177/0272989x9301300409 · Cited by 2,419 · see citing works

Knowledge-based analysis of microarray gene expression data by using support vector machines

Brown, M. P. S., Noble, W. S., Lin, D. M., Cristianini, N., Sugnet, C. W., Furey, T. S., Ares, M., & Haussler, D. H. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.1.262 · Cited by 2,310 · see citing works

Ensemble Methods: Foundations and Algorithms

Zhou, Z. (2012) · Cited by 2,051 · see citing works

MLlib: Machine Learning in Apache SparkPreprint

Meng, X., Bradley, J. K., Yavuz, B., Sparks, E., Venkataraman, S., Liu, D., Freeman, J., Tsai, D., Amde, M., Owen, S., et al. (2015) · Journal of machine learning research · doi:10.48550/arxiv.1505.06807 · Cited by 1,898 · see citing works

Apache Hadoop YARN: yet another resource negotiator

Vavilapalli, V. K., Murthy, A. C., Douglas, C., Agarwal, S., Konar, M., Evans, R., Graves, T., Lowe, J., Shah, H., Seth, S., et al. (2013) · Proceedings of the 4th annual Symposium on Cloud Computing · doi:10.1145/2523616.2523633 · Cited by 1,848 · see citing works

Hive

Thusoo, A., Sarma, J. S., Jain, N., Shao, Z., Chakka, P., Anthony, S., Liu, H., Wyckoff, P., & Murthy, R. (2009) · Proceedings of the VLDB Endowment · doi:10.14778/1687553.1687609 · Cited by 1,559 · see citing works

GPU Computing

Owens, J. D., Houston, M., Luebke, D. P., Green, S., Stone, J. E., & Phillips, J. C. (2008) · Proceedings of the IEEE · doi:10.1109/jproc.2008.917757 · Cited by 1,500 · see citing works

NVIDIA Tesla: A Unified Graphics and Computing Architecture

Lindholm, E., Nickolls, J. R., Oberman, S. F., & Montrym, J. S. (2008) · IEEE Micro · doi:10.1109/mm.2008.31 · Cited by 1,364 · see citing works

Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis

Barkhof, F. (1997) · Brain · doi:10.1093/brain/120.11.2059 · Cited by 1,251 · see citing works

Predicting breast cancer survivability: a comparison of three data mining methods

Delen, D., Walker, G., & Kadam, A. (2004) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2004.07.002 · Cited by 1,215 · see citing works

Apache flink : Stream and batch processing in a single engine

Carbone, P., Katsifodimos, A., Ewen, S., Markl, V., Haridi, S., & Tzoumas, K. (2015) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 1,137 · see citing works

Social Network Analysis

Scott, J. (1988) · Sociology · doi:10.1177/0038038588022001007 · Cited by 1,060 · see citing works

Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data

Denny, J. C., Bastarache, L. A., Ritchie, M. D., Carroll, R. J., Zink, R., Mosley, J. D., Field, J. R., Pulley, J. M., Ramirez, A. H., Bowton, E., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2749 · Cited by 978 · see citing works

Large scale deep learning for computer aided detection of mammographic lesions

Kooi, T., Litjens, G., van Ginneken, B., Gubern-Mérida, A., Sánchez, C. I., Mann, R., den Heeten, A., & Karssemeijer, N. (2017) · Medical Image Analysis · doi:10.1016/j.media.2016.07.007 · Cited by 965 · see citing works

Medical Internet of Things and Big Data in Healthcare

Dimitrov, D. V. (2016) · Healthcare Informatics Research · doi:10.4258/hir.2016.22.3.156 · Cited by 927 · see citing works

Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data

Zhang⋆, Y., Meikang Qiu, A., Tsai, C., Hassan, M. M., & Alamri, A. M. (2015) · IEEE Systems Journal · doi:10.1109/jsyst.2015.2460747 · Cited by 927 · see citing works

Charting a course for genomic medicine from base pairs to bedside

Green, E. D., & Guyer, M. S. (2011) · Nature · doi:10.1038/nature09764 · Cited by 901 · see citing works

Physicians’ Use Of Electronic Medical Records: Barriers And Solutions

Miller, R. H., & Sim, I. (2004) · Health Affairs · doi:10.1377/hlthaff.23.2.116 · Cited by 869 · see citing works

Big Data analytics

Singh, S., & Singh, N. (2012) · International Conference on Communication, Information & Computing Technology · doi:10.1109/iccict.2012.6398180 · Cited by 757 · see citing works

Predicting disease risks from highly imbalanced data using random forest

Khalilia, M. A., Chakraborty, S., & Popescu, M. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-51 · Cited by 727 · see citing works

Sensor networks for medical care

Shnayder, V., Chen, B.-R., Lorincz, K., Fulford-Jones, T. R. F., & Welsh, M. (2005) · ACM Conference on Embedded Networked Sensor Systems (SenSys) · doi:10.1145/1098918.1098979 · Cited by 723 · see citing works

AMON: A Wearable Multiparameter Medical Monitoring and Alert System

Anliker, U., Ward, J. A., Lukowicz, P., Troster, G., Dolveck, F., Baer, M., Keita, F., Schenker, E. B., Catarsi, F., Coluccini, L., et al. (2004) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2004.837888 · Cited by 707 · see citing works

Cyber-Physical Systems

Monostori, L. (2019) · Springer eBooks · doi:10.1007/978-3-662-53120-4_16790 · Cited by 684 · see citing works

Human Activity Recognition Using Wearable Sensors by Deep Convolutional Neural Networks

Jiang, W., & Yin, Z. (2015) · Proceedings of the 23rd ACM international conference on Multimedia · doi:10.1145/2733373.2806333 · Cited by 676 · see citing works

Adopting electronic medical records in primary care: Lessons learned from health information systems implementation experience in seven countries

LUDWICK, D., & DOUCETTE, J. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.06.005 · Cited by 668 · cited 1× · see citing works

EEG signals classification using the K-means clustering and a multilayer perceptron neural network model

Orhan, U., Hekim, M., & Özer, M. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.04.149 · Cited by 649 · see citing works

Genomic and personalized medicine: foundations and applications

Ginsburg, G. S., & Willard, H. F. (2009) · Translational Research · doi:10.1016/j.trsl.2009.09.005 · Cited by 637 · see citing works

Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms

Zheng, B., Yoon, S. W., & Lam, S. S. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.08.044 · Cited by 549 · see citing works

Big Data Analytics in Healthcare

Belle, A., Thiagarajan, R., Soroushmehr, S. M. R., Navidi, F., Beard, D. A., & Najarian, K. (2015) · BioMed Research International · doi:10.1155/2015/370194 · Cited by 527 · see citing works

High Performance Cluster Computing: Architectures and Systems

Buyya, R. (1999) · Prentice Hall PTR eBooks · Cited by 511 · see citing works

A survey on Data Mining approaches for Healthcare

Tomar, D., & Agarwal, S. (2013) · International Journal of Bio-Science and Bio-Technology · doi:10.14257/ijbsbt.2013.5.5.25 · Cited by 485 · see citing works

Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering

Gasch, A. P., & Eisen, M. B. (2002) · Genome biology · doi:10.1186/gb-2002-3-11-research0059 · Cited by 475 · see citing works

Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm

Ng, H. P., Ong, S. H., Foong, K. W. C., Goh, P. S., & Nowinski, W. L. (2006) · IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/ssiai.2006.1633722 · Cited by 468 · see citing works

Screening large-scale association study data: exploiting interactions using random forests

Lunetta, K. L., Hayward, B., Segal, J., & Eerdewegh, P. V. (2004) · BMC Genetics · doi:10.1186/1471-2156-5-32 · Cited by 464 · see citing works

Random forest-based similarity measures for multi-modal classification of Alzheimer's disease

Gray, K. R., Aljabar, P., Heckemann, R. A., Hammers, A., & Rueckert, D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.065 · Cited by 455 · see citing works

A survey on platforms for big data analytics

Singh, D., & Reddy, C. K. A. (2014) · Journal Of Big Data · doi:10.1186/s40537-014-0008-6 · Cited by 437 · see citing works

A real-time health monitoring system for remote cardiac patients using smartphone and wearable sensors

Kakria, P., Tripathi, N. K., & Kitipawang, P. (2015) · International Journal of Telemedicine and Applications · doi:10.1155/2015/373474 · Cited by 410 · see citing works

Defining architecture components of the Big Data Ecosystem

Demchenko, Y., de Laat, C., & Membrey, P. (2014) · International Conference on Collaboration Technologies and Systems (CTS) · doi:10.1109/cts.2014.6867550 · Cited by 409 · see citing works

Context-aware wireless sensor networks for assisted living and residential monitoring

Wood, A. D., Stankovic, J. A., Virone, G., Selavo, L., He, Z., Cao, Q., Doan, T., Wu, Y., Fang, L., & Stoleru, R. (2008) · IEEE Network · doi:10.1109/mnet.2008.4579768 · Cited by 409 · see citing works

SkewTune

Kwon, Y., Bałazińska, M., Howe, B., & Rolia, J. A. (2012) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/2213836.2213840 · Cited by 400 · see citing works

An Approach to Multimodal Biomedical Image Registration Utilizing Particle Swarm Optimization

Wachowiak, M. P., Smolikova, R., Zheng, Y., Żurada, J. M., & Elmaghraby, A. S. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826068 · Cited by 389 · see citing works

Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules

Anooj, P. (2011) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2011.09.002 · Cited by 384 · see citing works

Sentiment classification: The contribution of ensemble learning

Wang, G., Sun, J., Ma, J., Xu, K. S. J., & Gu, J. (2013) · Decision Support Systems · doi:10.1016/j.dss.2013.08.002 · Cited by 378 · see citing works

Intelligible Support Vector Machines for Diagnosis of Diabetes Mellitus

Barakat, N., Bradley, A. P., & Barakat, M. N. H. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2039485 · Cited by 367 · see citing works

A review of data mining using big data in health informatics

Herland, M., Khoshgoftaar, T. M., & Wald, R. (2014) · Journal Of Big Data · doi:10.1186/2196-1115-1-2 · Cited by 322 · see citing works

Impala: A Modern, Open-Source SQL Engine for Hadoop.

Kornacker, M., Behm, A., Bittorf, V., Bobrovytsky, T., Ching, C., Choi, A., Erickson, J., Grund, M., Hecht, D., Jacobs, M., et al. (2015) · Cited by 322 · see citing works

Mapping brain activity at scale with cluster computing

Freeman, J., Vladimirov, N., Kawashima, T., Mu, Y., Sofroniew, N. J., Bennett, D. V., Rosen, J., Yang, C.-T., Looger, L. L., & Ahrens, M. B. (2014) · Nature Methods · doi:10.1038/nmeth.3041 · Cited by 299 · see citing works

A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining

Islam, M. S., Hasan, M. M., Wang, X., Germack, H. D., & Noor‐E‐Alam, M. (2018) · Healthcare · doi:10.3390/healthcare6020054 · Cited by 268 · see citing works

MALDI Imaging Combined with Hierarchical Clustering as a New Tool for the Interpretation of Complex Human Cancers

Deininger, S., Ebert, M. P. A., Fütterer, A., Gerhard, M., & Röcken, C. (2008) · Journal of Proteome Research · doi:10.1021/pr8005777 · Cited by 266 · see citing works

Early diagnosis of Alzheimer?s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images

Khedher, L., Ramírez, J., Górriz, J. M., Brahim, A., & Segovia, F. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.09.072 · Cited by 262 · see citing works

Review of Cyber-Physical System in Healthcare

Haque, S. A., Aziz, S. M., & Rahman, M. (2014) · International Journal of Distributed Sensor Networks · doi:10.1155/2014/217415 · Cited by 262 · see citing works

On the Time Series $K$-Nearest Neighbor Classification of Abnormal Brain Activity

Chaovalitwongse, W. A., Fan, Y.-J., & Sachdeo, R. C. (2007) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/tsmca.2007.897589 · Cited by 221 · see citing works

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors

Razavian, N., Blecker, S., Schmidt, A. M., Smith–McLallen, A., Nigam, S., & Sontag, D. A. (2015) · Big Data · doi:10.1089/big.2015.0020 · Cited by 212 · see citing works

Computational Health Informatics in the Big Data Age: A Survey

Fang, R., Pouyanfar, S., Yang, Y., Chen, S.-C., & Iyengar, S. S. (2017) · ACM Computing Surveys · doi:10.1145/2932707 · Cited by 210 · see citing works

A fall detection system using k-nearest neighbor classifier

Liu, C., Lee, C.-H., & Lin, P.-M. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.04.014 · Cited by 205 · see citing works

Big data analytics for healthcare

Sun, J., & Reddy, C. K. A. (2013) · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2487575.2506178 · Cited by 196 · see citing works

Electronic Medical Records

Steward, M. (2005) · Journal of Legal Medicine · doi:10.1080/01947640500364762 · Cited by 191 · see citing works

Applying k-Nearest Neighbour in Diagnosing Heart Disease Patients

Shouman, M., Turner, T., & Stocker, R. (2012) · International Journal of Information and Education Technology · doi:10.7763/ijiet.2012.v2.114 · Cited by 190 · see citing works

Application of K-Means and Genetic Algorithms for Dimension Reduction by Integrating SVM for Diabetes Diagnosis

Santhanam, T., & Padmavathi, M. S. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.03.185 · Cited by 190 · see citing works

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis

van der Burgh, H. K., Schmidt, R., Westeneng, H., de Reus, M. A., van den Berg, L. H., & van den Heuvel, M. P. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.10.008 · Cited by 184 · see citing works

How to do (or not to do) ... a social network analysis in health systems research

Blanchet, K., & James, P. (2011) · Health Policy and Planning · doi:10.1093/heapol/czr055 · Cited by 176 · see citing works

Feature selection and classification model construction on type 2 diabetic patients’ data

Huang, Y., McCullagh, P. J., Black, N. D., & Harper, R. (2007) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2007.07.002 · Cited by 174 · see citing works

Modeling Medical Treatment Using Markov Decision Processes

Schaefer, A. J., Bailey, M. D., Shechter, S. M., & Roberts, M. S. (2005) · International Series in Operations Research & Management Science · doi:10.1007/1-4020-8066-2_23 · Cited by 155 · see citing works

Time to CARE: a collaborative engine for practical disease prediction

Davis, D. A., Chawla, N. V., Christakis, N. A., & Barabási, A.-Ĺ. (2009) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-009-0156-z · Cited by 146 · see citing works

Fast GPU-Based CT Reconstruction using the Common Unified Device Architecture (CUDA)

Scherl, H., Keck, B., Kowarschik, M., & Joachim Hornegger, A. (2007) · IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) · doi:10.1109/nssmic.2007.4437102 · Cited by 138 · see citing works

Large-scale compression of genomic sequence databases with the Burrows–Wheeler transform

Cox, A. J., Bauer, M. J., Jakobi, T., & Rosone, G. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts173 · Cited by 135 · see citing works

A new hybrid approach for mining breast cancer pattern using discrete particle swarm optimization and statistical method

Yeh, W., Chang, W.-W., & Chung, Y. Y. (2008) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.10.004 · Cited by 134 · see citing works

Enlighten Wearable Physiological Monitoring Systems: On-Body RF Characteristics Based Human Motion Classification Using a Support Vector Machine

Geng, Y., Chen, J., Fu, R., Bao, G., & Pahlavan, K. (2015) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2015.2416186 · Cited by 134 · see citing works

Health big data analytics: current perspectives, challenges and potential solutions

Kuo, M. H., Sahama, T. R., Kushniruk, A. W., Borycki, E. M., & Grunwell, D. (2014) · International Journal of Big Data Intelligence · doi:10.1504/ijbdi.2014.063835 · Cited by 133 · see citing works

Data mining with decision trees for diagnosis of breast tumor in medical ultrasonic images

Kuo, W.-J., Chang, R., Chen, D., & Lee, C. C. (2001) · Breast Cancer Research and Treatment · doi:10.1023/a:1010676701382 · Cited by 132 · see citing works

MongoDB in Action

Banker, K. (2011) · Cited by 123 · see citing works

HL7 RIM: an incoherent standard.

Smith, B., & Ceusters, W. M. (2006) · PubMed · Cited by 123 · see citing works

Cyber-Physical Systems

acatech - National Academy of Science and Engineering, 2. (2011) · Springer eBooks · doi:10.1007/978-3-642-29090-9 · Cited by 122 · see citing works

Incidence and morbidity of cholelithiasis in patients receiving chronic octreotide for metastatic carcinoid and malignant islet cell tumors

Trendle, M. C., Moertel, C. G., & Kvols, L. K. (1997) · Cancer · doi:10.1002/(sici)1097-0142(19970215)79:4 · Cited by 120 · see citing works

High performance computing for deformable image registration: Towards a new paradigm in adaptive radiotherapy

Samant, S. S., Xia, J., Muyan‐Özçelik, P., & Owens, J. D. (2008) · Medical Physics · doi:10.1118/1.2948318 · Cited by 119 · see citing works

COPA—cancer outlier profile analysis

MacDonald, J. W., & Ghosh, D. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl433 · Cited by 117 · see citing works

GPU-based ultrafast IMRT plan optimization

Men, C., Gu, X., Choi, D., Majumdar, A., Zheng, Z., Mueller, K. D., & Jiang, S. B. (2009) · Physics in Medicine and Biology · doi:10.1088/0031-9155/54/21/008 · Cited by 115 · see citing works

SparkSeq: fast, scalable and cloud-ready tool for the interactive genomic data analysis with nucleotide precision

Wiewiórka, M. S., Messina, A., Pacholewska, A., Maffioletti, S., Gawrysiak, P., & Okoniewski, M. J. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu343 · Cited by 108 · see citing works

Survival prediction in Amyotrophic lateral sclerosis based on MRI measures and clinical characteristics

Schuster, C., Hardiman, O. M., & Bede, P. (2017) · BMC Neurology · doi:10.1186/s12883-017-0854-x · Cited by 108 · see citing works

Machine-learning-based classification of real-time tissue elastography for hepatic fibrosis in patients with chronic hepatitis B

Chen, Y., Luo, Y., Huang, W., Hu, D., Zheng, R., Cong, S., Meng, F.-K., Yang, H., Lin, H.-J., Sun, Y., et al. (2017) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2017.07.012 · Cited by 105 · see citing works

Fully 3D list‐mode time‐of‐flight PET image reconstruction on GPUs using CUDA

Cui, J., Pratx, G., Prevrhal, S., & Levin, C. S. (2011) · Medical Physics · doi:10.1118/1.3661998 · Cited by 102 · see citing works

Using the K-Nearest Neighbor Algorithm for the Classification of Lymph Node Metastasis in Gastric Cancer

Li, C., Zhang, S., Zhang, H., 庞丽芳, Lam, K., Hui, C., & Zhang, S. (2012) · Computational and Mathematical Methods in Medicine · doi:10.1155/2012/876545 · Cited by 100 · see citing works

Effective Diagnosis of Heart Disease through Bagging Approach

Tu, M. C., Shin, D., & Shin, D. (2009) · International Conference on Biomedical Engineering and Informatics (BMEI) · doi:10.1109/bmei.2009.5301650 · Cited by 99 · see citing works

Big data solutions for predicting risk-of-readmission for congestive heart failure patients

Zolfaghar, K., Meadem, N., Teredesai, A. M., Roy, S. B., Chin, S.-C., & Muckian, B. (2013) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2013.6691760 · Cited by 87 · see citing works

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis

Moreno-Conde, A., Moner, D., Cruz, W. D. D., dos Santos, M. R., Maldonado, J. A., Robles, M., & Kalra, D. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv008 · Cited by 86 · see citing works

Design and Development of a Medical Big Data Processing System Based on Hadoop

Yao, Q., Tian, Y., Li, P., Tian, L., Qian, Y., & Li, J. (2015) · Journal of Medical Systems · doi:10.1007/s10916-015-0220-8 · Cited by 85 · see citing works

The genome-enabled electronic medical record

Hoffman, M. A. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.02.010 · Cited by 85 · see citing works

Empirically Derived Decision Trees for the Treatment of Late-Life Depression

Andreescu, C., Mulsant, B. H., Houck, P. R., Whyte, E. M., Mazumdar, S., Dombrovski, A. Y., Pollock, B. G., & Reynolds, C. F. (2008) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2008.07081340 · Cited by 82 · see citing works

Predicting breast cancer survivability using fuzzy decision trees for personalized healthcare

Khan, M. U., Choi, J. P., Shin, H., & Kim, M. (2008) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2008.4650373 · Cited by 80 · see citing works

BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data

Andrio, P., Cugnasco, C., Codó, L., Becerra, Y., Dans, P. D., Battistini, F., Torres, J., Goñi, R., Orozco, M., & Gelpí, J. L. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1301 · Cited by 78 · see citing works

Big Data in Medical Applications and Health Care

Wang, L., & Alexander, C. A. (2015) · Current Research in Medicine · doi:10.3844/amjsp.2015.1.8 · Cited by 65 · see citing works

The NoSQL Principles and Basic Application of Cassandra Model

Wang, G., & Tang, J. (2012) · International Conference on Computer Science and Service System · doi:10.1109/csss.2012.336 · Cited by 64 · see citing works

Artificial neural networks for automatic segmentation and identification of nasopharyngeal carcinoma

Mohammed, M. A., Ghani, M. K. A., Hamed, R. I., Ibrahim, D. A., & Abdullah, M. K. (2017) · Journal of Computational Science · doi:10.1016/j.jocs.2017.03.026 · Cited by 62 · see citing works

A Reconfigurable, Wearable, Wireless ECG System

Borromeo, S., Rodriguez‐Sanchez, M. C., Machado, F., Hernandez-Tamames, J., & de la Prieta, R. (2007) · Conference proceedings · doi:10.1109/iembs.2007.4352626 · Cited by 59 · see citing works

Big Data Approaches for the Analysis of Large-Scale fMRI Data Using Apache Spark and GPU Processing: A Demonstration on Resting-State fMRI Data from the Human Connectome Project

Boubela, R., Kalcher, K., Huf, W., Nasel, C., & Moser, E. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00492 · Cited by 56 · see citing works

Chronic Diseases and Health Monitoring Big Data: A Survey

Lin, R., Ye, Z., Wang, H. H., & Wu, B. (2018) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2018.2829704 · Cited by 56 · see citing works

Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI

Savio, A. M., García‐Sebastián, M., Chyzhyk, D., Hernández, C., Graña, M., Sistiaga, A., de Munaín, A. L., & Villanúa, J. (2011) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2011.05.010 · Cited by 53 · see citing works

A cloud computing solution for Hospital Information System

He, C., Jin, X., Zhao, Z., & Xiang, T. (2010) · IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS) · doi:10.1109/icicisys.2010.5658278 · Cited by 46 · see citing works

Risk factors for persistent frequent use of the primary health care services among frequent attenders: A Bayesian approach

Koskela, T., Ryynänen, O., & Soini, E. J. (2010) · Scandinavian Journal of Primary Health Care · doi:10.3109/02813431003690596 · Cited by 44 · see citing works

Distributed data-driven platform for urgent decision making in cardiological ambulance control

Kovalchuk, S. V., Krotov, E., Smirnov, P. A., Nasonov, D. A., & Yakovlev, A. N. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.09.017 · Cited by 43 · see citing works

Managing Skew in Hadoop.

Kwon, Y., Ren, K., Bałazińska, M., & Howe, B. (2013) · Cited by 41 · see citing works

Data Analytics in Ubiquitous Sensor-Based Health Information Systems

Mukherjee, A., Pal, A., & Misra, P. (2012) · 2012 Sixth International Conference on Next Generation Mobile Applications, Services and Technologies · doi:10.1109/ngmast.2012.39 · Cited by 35 · see citing works

Integration of genomics into the electronic health record: mapping terra incognita

Kannry, J. L., & Williams, M. S. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.102 · Cited by 34 · see citing works

An Architecture and Reference Implementation of an Open Health Information Mediator: Enabling Interoperability in the Rwandan Health Information Exchange

Crichton, R., Moodley, D., Pillay, A. W., Gakuba, R., & Seebregts, C. J. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39088-3_6 · Cited by 32 · see citing works

Hadoop Architecture and Its Issues

Alam, A., & Ahmed, J. (2014) · International Conference on Computational Science and Computational Intelligence (CSCI) · doi:10.1109/csci.2014.140 · Cited by 31 · see citing works

THE CLINICAL BIOINFORMATICS ONTOLOGY: A CURATED SEMANTIC NETWORK UTILIZING REFSEQ INFORMATION

Hoffman, M. A., Arnoldi, C., & CHUANG, I. (2004) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789812702456_0014 · Cited by 30 · see citing works

Architectural frameworks for developing national health information systems in low and middle income countries

Mudaly, T., Moodley, D., Pillay, A. W., & Seebregts, C. J. (2013) · International Conference on Enterprise Systems (ES) · doi:10.1109/es.2013.6690083 · Cited by 29 · see citing works

Application of cloud computing in the health information system

Wang, X., & Tan, Y. (2010) · International Conference on Computer Application and System Modeling · doi:10.1109/iccasm.2010.5619051 · Cited by 28 · see citing works

Distributed and hardware accelerated computing for clinical medical imaging using proton computed tomography (pCT)

Karonis, N. T., Duffin, K. L., Ordoñez, C. E., Erdelyi, B., Uram, T. D., Olson, E. C., Coutrakon, G. B., & Papka, M. E. (2013) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2013.07.016 · Cited by 28 · see citing works

A clinical use case to evaluate the i2b2 Hive: predicting asthma exacerbations.

Meystre, S. M., Deshmukh, V. G., & Mitchell, J. A. (2009) · Europe PMC (PubMed Central) · Cited by 22 · see citing works

Design and Construction of a Big Data Analytics Framework for Health Applications

Kuo, M.-H., Chrimes, D., Moa, B., & Hu, W. P. (2015) · IEEE International Conference on Smart City/SocialCom/SustainCom · doi:10.1109/smartcity.2015.140 · Cited by 22 · see citing works

Field Programmable Gate Arrays

Bailey, D. G. (2011) · doi:10.1002/9780470828519.ch2 · Cited by 18 · see citing works

An ensemble classifier based prediction of G-protein-coupled receptor classes in low homology

Gu, Q., Ding, Y., & Zhang, T.-L. (2015) · Neurocomputing · doi:10.1016/j.neucom.2014.12.013 · Cited by 18 · see citing works

A Comparison of National Health Data Interoperability Approaches in Taiwan, Denmark and Canada

Kuo, M.-H., Kushniruk, A. W., & Borycki, E. M. (2011) · UVic’s Research and Learning Repository (University of Victoria) · Cited by 17 · see citing works

Middleware for Wireless Medical Body Area Network

Waluyo, A. B., Song, Y., Pek, I., & Wu, J. K. (2007) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2007.4463339 · Cited by 17 · see citing works

Field of genes: using Apache Kafka as a bioinformatic data repository

Lawlor, B., Lynch, R. M., Aogáin, M. M., & Walsh, P. (2018) · GigaScience · doi:10.1093/gigascience/giy036 · Cited by 16 · see citing works

Towards a 'Big' Health Data Analytics Platform

Cha, S., AbuSharekh, A. M., & Abidi, S. S. R. (2015) · IEEE International Conference on Big Data Computing Service and Applications (BigDataService) · doi:10.1109/bigdataservice.2015.13 · Cited by 15 · see citing works

BBN-Based Decision Support for Health Risk Analysis

Liu, K. F. R., & Lu, C.-F. (2009) · doi:10.1109/ncm.2009.187 · Cited by 15 · see citing works

Electronic medical records

Potts, J. F. (1997) · Postgraduate Medicine · doi:10.3810/pgm.1997.02.154 · Cited by 13 · see citing works

Medoop: A medical information platform based on Hadoop

Lijun, W., Huang, Y., Chen, J., Zhou, K., & Li, C. (2013) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2013.6720779 · Cited by 12 · see citing works

Semantic-based data integration model applied to heterogeneous medical information system

Shi, Y., Liu, X., Xu, Y., & Ji, Z. (2010) · International Conference on Computer and Automation Engineering · doi:10.1109/iccae.2010.5451697 · Cited by 12 · see citing works

Social Media Analytics for Healthcare

Kotov, A. (2015) · doi:10.13140/rg.2.1.2301.8409 · Cited by 12 · see citing works

An analysis of modeling flaws in HL7 and JAHIS

Fernández, E. B., & Sorgente, T. (2005) · ACM Symposium on Applied Computing · doi:10.1145/1066677.1066732 · Cited by 9 · see citing works

An activity monitoring system for detecting movement by a person lying on a bed

Hanada, E., Seo, T., & Hata, H. (2013) · IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin) · doi:10.1109/icce-berlin.2013.6697968 · Cited by 9 · see citing works

Parallelized text classification algorithm for processing large scale TCM clinical data with MapReduce

Fei, X., Li, X., & Shen, C. (2015) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2015.7279613 · Cited by 8 · see citing works

chitSMS: Community Health Information Tracking System Using Short Message Service

Manguni, R., Navarro, M. L., Rosario, K., & Festin, C. A. M. (2010) · International Conference on Human-Centric Computing (HumanCom) · doi:10.1109/humancom.2010.5563329 · Cited by 8 · see citing works

Scalable genomics: From raw data to aligned reads on Apache YARN

Versaci, F., Pireddu, L., & Zanetti, G. (2016) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2016.7840727 · Cited by 8 · see citing works

Design of middleware for tele‐homecare systems

Lu, H., & Chen, J.-L. (2009) · Wireless Communications and Mobile Computing · doi:10.1002/wcm.739 · Cited by 8 · see citing works

Middleware for healthcare information systems.

Spahni, S., Scherrer, J.-R., Sauquet, D., & Sottile, P. A. (1998) · PubMed · Cited by 7 · see citing works

Middleware for remote healthcare monitoring

Leite, C. R. M., de Araújo, B. G., Valentim, R. A. D. M., Brandão, G. B., & Gueirreiro, A. M. G. (2009) · International Conference on Innovations in Information Technology · doi:10.1109/iit.2009.5413781 · Cited by 7 · see citing works

AEGLE: A big bio-data analytics framework for integrated health-care services

Soudris, D., Xydis, S., Baloukas, C., Hadzidimitriou, A., Chouvarda, I., Σταματόπουλος, Κ., Maglaveras, N., Chang, J., Raptopoulos, A., Manset, D., et al. (2015) · International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation · doi:10.1109/samos.2015.7363682 · Cited by 7 · see citing works

Activity and health status monitoring system

Oniga, S., Tisan, A., & Bolyi, R. (2017) · IEEE International Symposium on Industrial Electronics (ISIE) · doi:10.1109/isie.2017.8001566 · Cited by 7 · see citing works

A Social Network Analysis Framework for Modeling Health Insurance Claims DataPreprint

Appel, A. P., de Santana, V. F., Moyano, L. G., Ito, M., & Pinhanez, C. S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.07116 · Cited by 7 · see citing works

Towards Collaborative Health Care System Model - COHESY

Vlahu‐Gjorgievska, E., & Trajkovik, V. (2011) · IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) · doi:10.1109/wowmom.2011.5986197 · Cited by 6 · see citing works

Integrating Social Media and Mobile Sensor Data for Clinical Decision Support: Concept and Requirements

Denecke, K. (2016) · PubMed · doi:10.24451/arbor.7656 · Cited by 6 · see citing works

Development of a Health Information System in the Mobile Cloud Environment

Wan, J., & Sankaranarayanan, S. (2013) · doi:10.1109/hpcc.and.euc.2013.313 · Cited by 5 · see citing works

Home Healthcare Staff Scheduling: A Clustering Particle Swarm Optimization Approach

Mutingi, M., & Mbohwa, C. (2014) · Cited by 4 · see citing works

Social contagion and technology adoption: a study in healthcare professionals.

Zheng, K., Padman, R., & Johnson, M. P. (2007) · PubMed · Cited by 4 · see citing works

Low Power Tracking System for Advanced Health Monitoring

Rouet, V., & Venet, J. (2008) · Integration Issues of Miniaturized Systems - MOMS, MOEMS, ICS and Electronic Components (SSI), 2008 2nd European Conference & Exhibition on · Cited by 2 · see citing works

Design and Implementation of Electronic Medical Record Template Based on XML Schema

Yang, H. (2010) · World Congress on Software Engineering (WCSE) · doi:10.1109/wcse.2010.134 · Cited by 2 · see citing works

Federated Learning for Internet of Things: A Comprehensive Survey

Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., & Vincent Poor, H. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3075439 · Cited by 1,503 · see citing works

The ethics of AI in health care: A mapping review

Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020) · Social Science & Medicine · doi:10.1016/j.socscimed.2020.113172 · Cited by 1,105 · see citing works

Federated Learning for Internet of Things: A Comprehensive Survey

Nguyen, D., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., & Poor, H. (2021) · Deakin Research Online (Deakin University) · Cited by 889 · see citing works

The use of Big Data Analytics in healthcare

Batko, K. M., & Ślęzak, A. (2022) · Journal Of Big Data · doi:10.1186/s40537-021-00553-4 · Cited by 600 · see citing works

Big data analytics in healthcare: a systematic literature review

Khanra, S., Dhir, A., Islam, A. K. M. N., & Mäntymäki, M. (2020) · Enterprise Information Systems · doi:10.1080/17517575.2020.1812005 · Cited by 292 · see citing works

Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms

Giovanola, B., & Tiribelli, S. (2023) · AI & SOCIETY · doi:10.1007/s00146-022-01455-6 · Cited by 193 · see citing works

Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care

Parviainen, J., & Rantala, J. (2022) · Medicine, Health Care and Philosophy · doi:10.1007/s11019-021-10049-w · Cited by 146 · see citing works

A Framework for Pandemic Prediction Using Big Data Analytics

Ahmed, I., Ahmad, M., Jeon, G., & Piccialli, F. (2021) · Big Data Research · doi:10.1016/j.bdr.2021.100190 · Cited by 126 · see citing works

A comprehensive survey on federated learning techniques for healthcare informatics

Dasaradharami Reddy, K., & Gadekallu, T. R. (2023) · Computational Intelligence and Neuroscience · doi:10.1155/2023/8393990 · Cited by 126 · see citing works

The role and impact of new technologies on healthcare systems

Sinha, R. K. (2024) · Discover Health Systems · doi:10.1007/s44250-024-00163-w · Cited by 113 · see citing works

Leveraging 6G, extended reality, and IoT big data analytics for healthcare: A review

Ahmad, H. F., Rafique, W., Rasool, R. U., Alhumam, A., Anwar, Z., & Qadir, J. (2023) · Computer Science Review · doi:10.1016/j.cosrev.2023.100558 · Cited by 96 · see citing works

An Open IoHT-Based Deep Learning Framework for Online Medical Image Recognition

Dourado, C. M. J. D. M., da Silva, S. P. P., da Nóbrega, R. V. M., Filho, P. P. R., Muhammad, K., & de Albuquerque, V. H. C. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3020598 · Cited by 94 · see citing works

A new emergency decision support system: the automatic interpretation and contextualisation of events to model a crisis situation in real-time

Fertier, A., Barthe‐Delanoë, A., Montarnal, A., Truptil, S., & Bénaben, F. (2020) · Decision Support Systems · doi:10.1016/j.dss.2020.113260 · Cited by 80 · see citing works

Towards Secure and Intelligent Internet of Health Things: A Survey of Enabling Technologies and Applications

Zaman, U., Imran, I., Mehmood, F., Iqbal, N., Kim, J., & Ibrahim, M. (2022) · Electronics · doi:10.3390/electronics11121893 · Cited by 76 · see citing works

Machine Learning and Big Data Implementation on Health Care data

Sasubilli, G., & Kumar, A. (2020) · International Conference on Intelligent Computing and Control Systems (ICICCS) · doi:10.1109/iciccs48265.2020.9120906 · Cited by 68 · see citing works

An ethically mindful approach to AI for health care

Morley, J., & Floridi, L. (2020) · The Lancet · doi:10.1016/s0140-6736(19)32975-7 · Cited by 69 · see citing works

The Debate on the Ethics of AI in Health Care: a Reconstruction and Critical Review

Morley, J., Machado, C., Burr, C., Cowls, J., Taddeo, M., & Floridi, L. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3486518 · Cited by 66 · see citing works

A Systematic Review of Healthcare Big Data

Raja, R., Mukherjee, I., & Sarkar, B. K. (2020) · Scientific Programming · doi:10.1155/2020/5471849 · Cited by 64 · see citing works

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

Singh, R. K., Agrawal, S., Sahu, A., & Kazançoğlu, Y. (2021) · The TQM Journal · doi:10.1108/tqm-02-2021-0051 · Cited by 64 · see citing works

Healthcare IoT-Based Affective State Mining Using a Deep Convolutional Neural Network

Alam, M. G. R., Abedin, S. F., Moon, S. I., Talukder, A., & Hong, C. S. (2019) · IEEE Access · doi:10.1109/access.2019.2919995 · Cited by 62 · see citing works

Enhancing Digital Health Services with Big Data Analytics

Berros, N., Elmendili, F., Filaly, Y., & Idrissi, Y. E. B. E. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7020064 · Cited by 61 · see citing works

BigData Analysis in Healthcare: Apache Hadoop , Apache spark and Apache Flink

Nazari, E., Shahriari, M. H., & Tabesh, H. (2019) · Frontiers in Health Informatics · doi:10.30699/fhi.v8i1.180 · Cited by 59 · see citing works

15 years of Big Data: a systematic literature review

Tosi, D., Kokaj, R., & Roccetti, M. (2024) · Journal Of Big Data · doi:10.1186/s40537-024-00914-9 · Cited by 59 · see citing works

Machine Learning-Based Asthma Risk Prediction Using IoT and Smartphone Applications

Bhat, G. S., Shankar, N., Kim, D., Song, D. J., Seo, S., Panahi, I. M. S., & Tamil, L. S. (2021) · IEEE Access · doi:10.1109/access.2021.3103897 · Cited by 54 · see citing works

Data Work of Frontline Care Workers: Practices, Problems, and Opportunities in the Context of Data-Driven Long-Term Care

Sun, Y., Ma, X., Lindtner, S., & He, L. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579475 · Cited by 56 · see citing works

Predicting Asthma Attacks: Effects of Indoor PM Concentrations on Peak Expiratory Flow Rates of Asthmatic Children

Kim, D., Cho, S.-H., Tamil, L. S., Song, D. J., & Seo, S. (2019) · IEEE Access · doi:10.1109/access.2019.2960551 · Cited by 53 · see citing works

A contemporary survey of recent advances in federated learning: Taxonomies, applications, and challenges

Alsharif, M. H., Kannadasan, R., Wei, W., Nisar, K. S., & Abdel‐Aty, A. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101251 · Cited by 52 · see citing works

A systematic review on big data applications and scope for industrial processing and healthcare sectors

Rahul, K., Banyal, R. K., & Arora, N. K. (2023) · Journal Of Big Data · doi:10.1186/s40537-023-00808-2 · Cited by 55 · see citing works

A Systematic Literature Review of Enabling IoT in Healthcare: Motivations, Challenges, and Recommendations

Jawad, H. H. M., Hassan, Z., Zaidan, B. B., Jawad, F. H. M., Jawad, D. H. M., & Alredany, W. H. D. (2022) · Electronics · doi:10.3390/electronics11193223 · Cited by 43 · see citing works

The Ethics of AI in Health Care: A Mapping Review

Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020) · Philosophical studies series · doi:10.1007/978-3-030-81907-1_18 · Cited by 141 · see citing works

PRECISION MEDICINE AND GENOMICS: A COMPREHENSIVE REVIEW OF IT-ENABLED APPROACHES

Udegbe, F. C., Ebulue, O. R., Ebulue, C. C., & Ekesiobi, C. S. (2024) · International Medical Science Research Journal · doi:10.51594/imsrj.v4i4.1053 · Cited by 36 · see citing works

Biomedical Signals for Healthcare Using Hadoop Infrastructure with Artificial Intelligence and Fuzzy Logic Interpretation

Selvarajan, S., Manoharan, H., Hasanin, T., Alsini, R. A. I., Uddin, M., Shorfuzzaman, M., & Alsufyani, A. (2022) · Applied Sciences · doi:10.3390/app12105097 · Cited by 35 · see citing works

Is There a Place for Responsible Artificial Intelligence in Pandemics? A Tale of Two Countries

El-Haddadeh, R., Fadlalla, A. M., & Hindi, N. M. (2021) · Information Systems Frontiers · doi:10.1007/s10796-021-10140-w · Cited by 28 · see citing works

Toward a smart health: big data analytics and IoT for real-time miscarriage prediction

Asri, H., & Jarir, Z. (2023) · Journal Of Big Data · doi:10.1186/s40537-023-00704-9 · Cited by 27 · see citing works

Autonomous and Sustainable Service Economies: Data-Driven Optimization of Design and Operations through Discovery of Multi-Perspective Parameters

Alahmari, N., Mehmood, R., Alzahrani, A., Yiğitcanlar, T., & Corchado, J. M. (2023) · Sustainability · doi:10.3390/su152216003 · Cited by 31 · see citing works

Reliable Federated Learning Systems Based on Intelligent Resource Sharing Scheme for Big Data Internet of Things

Math, S., Tam, P., & Kim, S. (2021) · IEEE Access · doi:10.1109/access.2021.3101871 · Cited by 26 · see citing works

Big Data Insights and Comprehensions in Industrial Healthcare: An Overview

He, W., Nazir, S., & Hussain, Z. (2021) · Mobile Information Systems · doi:10.1155/2021/6628739 · Cited by 25 · see citing works

Big data analytics in healthcare: data sources, tools, challenges, and opportunities

Badawy, M., Ramadan, N., & Hefny, H. A. (2024) · Journal of Electrical Systems and Information Technology · doi:10.1186/s43067-024-00190-w · Cited by 23 · see citing works

Big-Data and Cyber-Physical Systems in Healthcare: Challenges and Opportunities

Cabello, J. C., Karimipour, H., Jahromi, A. N., Dehghantanha, A., & Parizi, R. M. (2020) · Springer eBooks · doi:10.1007/978-3-030-38557-6_12 · Cited by 22 · see citing works

Application of Big Data Analytics and Internet of Medical Things (IoMT) in Healthcare with View of Explainable Artificial Intelligence: A Survey

Sinha, A., Garcia, D. W., Kumar, B., & Banerjee, P. (2023) · Internet of things · doi:10.1007/978-3-031-08637-3_8 · Cited by 22 · see citing works

Digital social innovation based on Big Data Analytics for health and well-being of society

Batko, K. M. (2023) · Journal Of Big Data · doi:10.1186/s40537-023-00846-w · Cited by 22 · see citing works

Development of Novel Big Data Analytics Framework for Smart Clothing

Ahsan, M., Teay, S. H., & Albarbar, A. (2020) · IEEE Access · doi:10.1109/access.2020.3015152 · Cited by 21 · see citing works

Big data analytics in healthcare: current practices, innovations, and future prospects

Shahzad, K., Khan, S. A., Latif, M., Javeed, A. M. D., & Iqbal, A. (2025) · Journal Of Big Data · doi:10.1186/s40537-025-01288-2 · Cited by 20 · see citing works

Advancing Federated Learning: A Systematic Literature Review of Methods, Challenges, and Applications

Sana, T. Z., Abdulla, S., Nag, A., Das, A., Hassan, M. M., Fiza, Z. Z., Karim, A., & Kabir, S. R. R. (2025) · IEEE Access · doi:10.1109/access.2025.3605165 · Cited by 21 · see citing works

Health data hubs: an analysis of existing data governance features for research

Álvarez-Romero, C., Martínez-García, A., Bernabeu‐Wittel, M., & Parra-Calderón, C. L. (2023) · Health Research Policy and Systems · doi:10.1186/s12961-023-01026-1 · Cited by 19 · see citing works

Classification of clustered health care data analysis using generative adversarial networks (GAN)

Purandhar, N., Ayyasamy, S., & Sivakumar, P. (2022) · Soft Computing · doi:10.1007/s00500-022-07026-7 · Cited by 17 · see citing works

A Review of Big Data Trends and Challenges in Healthcare

Baloch, L., Bazai, S. U., Marjan, S., Aftab, F., Aslam, S., Neo, T., & Amphawan, A. (2023) · International Journal of Technology · doi:10.14716/ijtech.v14i6.6643 · Cited by 17 · see citing works

Big Data Analytics and Processing Platform in Czech Republic Healthcare

Štufi, M., Bačić, B., & Stoimenov, L. V. (2020) · Applied Sciences · doi:10.3390/app10051705 · Cited by 17 · see citing works

Machine learning and clinical EEG data for multiple sclerosis: A systematic review

Mouazen, B., Bendaouia, A., Abdelwahed, E. H., & de Marco, G. (2025) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2025.103116 · Cited by 16 · see citing works

Patient-Provider Interaction System for Efficient Home-Based Cardiac Rehabilitation Exercise

Chung, H., Lee, H., Kim, C., Hong, S., & Lee, J. (2019) · IEEE Access · doi:10.1109/access.2019.2892717 · Cited by 14 · see citing works

Efficient Big-Data Access: Taxonomy and a Comprehensive Survey

Alazzawe, A., Pal, A., & Kant, K. (2020) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2020.3036813 · Cited by 13 · see citing works

The Debate on the Ethics of AI in Health Care: a Reconstruction and Critical ReviewPreprint

Morley, J. (2019) · doi:10.31219/osf.io/n7y2g · Cited by 12 · see citing works

Develop the hybrid Adadelta Stochastic Gradient Classifier with optimized feature selection algorithm to predict the heart disease at earlier stage

Senthil, R., Narayanan, B., & Velmurugan, K. (2022) · Measurement Sensors · doi:10.1016/j.measen.2022.100602 · Cited by 12 · see citing works

Reviewing big data's role in the digital economy: USA and Africa focus

Adeleye, R. A., Awonuga, K. F., Ndubuisi, N. L., Oyeyemi, O. P., & Asuzu, O. F. (2024) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2024.21.2.0396 · Cited by 11 · see citing works

Ordinal Optimization-Based Performance Model Estimation Method for HDFS

Ma, T., Tian, F., & Dong, B. (2019) · IEEE Access · doi:10.1109/access.2019.2962724 · Cited by 11 · see citing works

Implementing Fog Computing for Detecting Primary Tumors Using Hybrid Approach of Data Mining

Singh, J., Kad, S., & Singh, P. (2021) · Springer proceedings in energy · doi:10.1007/978-981-16-0235-1_83 · Cited by 10 · see citing works

A Review on Data Mining Techniques and Challenges in Medical Field

Reddy, R. A., & GNITS (2020) · International Journal of Engineering Research and · doi:10.17577/ijertv9is080143 · Cited by 8 · see citing works

Blockchain-based Security for Internet of Medical Things Application

Ramzan, T., & Zafar, S. (2022) · International Conference on Cyber Warfare and Security (ICCWS) · doi:10.1109/iccws56285.2022.9998443 · Cited by 8 · see citing works

Machine Learning Decision Support for Macronutrients in Neonatal Parenteral Nutrition

Derakhshandara, S., Franzoni, V., Mezzetti, D., & Poggioni, V. (2024) · IEEE Access · doi:10.1109/access.2024.3498059 · Cited by 8 · see citing works

Implementation of Artificial Intelligence in Disease Prediction and Healthcare System- A Survey

Deeba, F., & Patil, S. R. (2021) · Innovations in Power and Advanced Computing Technologies (i-PACT) · doi:10.1109/i-pact52855.2021.9696698 · Cited by 7 · see citing works

IoT based Big data Analytics in Healthcare: A Survey

M, A. S., Ramesh, K., & S, S. S. (2021) · International Conference on Advanced Scientific Innovation in Science, Engineering and Technology (ICASISET) · doi:10.4108/eai.16-5-2020.2304020 · Cited by 7 · see citing works

Foresights for big data across industries

Almeida, F. L. (2022) · foresight · doi:10.1108/fs-02-2021-0059 · Cited by 7 · see citing works

Big Data in Healthcare: A Review

Goyal, I., Singh, A., & Saini, J. K. (2022) · International Conference on Informatics (ICI) · doi:10.1109/ici53355.2022.9786918 · Cited by 7 · see citing works

The barriers and prospects related to big data analytics implementation in public institutions: a systematic review analysis

(2023) · International Journal of Advanced Computer Research · doi:10.19101/ijacr.2021.1152071 · Cited by 7 · see citing works

Intelligent Big Data Analytics in Health

Bayrak, E. A., & Kirci, P. (2019) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-5225-8567-1.ch014 · Cited by 7 · see citing works

Deformation and Refined Features Based Lesion Detection on Chest X-Ray

Li, C., Zhang, D., Du, S., & Tian, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2963926 · Cited by 7 · see citing works

Homecare interventions as a Service model for Obstructive sleep Apnea: Delivering personalised phone call using patient profiling and adherence predictions

Joymangul, J. S., Sekhari, A., Grasset, O., & Moalla, N. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104935 · Cited by 6 · see citing works

Big data and predictive analytics and Malaysian micro-, small and medium businesses

Vachkova, M., Ghouri, A. M., Ashour, H., Isa, N. B. M., & Barnes, G. (2023) · SN Business & Economics · doi:10.1007/s43546-023-00528-y · Cited by 12 · see citing works

Real-Time Visual Analytics for Remote Monitoring of Patient’s Health

Boumrah, M., Garbaya, S., & Radgui, A. (2023) · Computer Science Research Notes · doi:10.24132/csrn.3301.61 · Cited by 5 · see citing works

The Role of Machine Learning in Big Data Analytics: Current Practices and Challenges

Duran-Limon, H. A., Chavoya, A., & Hernández-Ochoa, M. (2023) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-031-40956-1_2 · Cited by 5 · see citing works

Blockchain Technologies in Data Science: Challenges and Benefits

Laboso, P. K., Martin, A., & Thiyagarajan, P. (2023) · International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) · doi:10.1109/icscds56580.2023.10104674 · Cited by 4 · see citing works

UAV Application With XAI and Soft Computing Methods to Protect Privacy of Power-Data in Smart Grids

Gan, Y., Xiao, Z., Ke, T., & Liang, Z. (2025) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2025.3551519 · Cited by 3 · see citing works

Behavior Intention of Chronic Illness Patients in Malaysia to Use IoT-based Healthcare Services

Jawad, H. H. M., Hassan, Z., & Zaidan, B. B. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140659 · Cited by 3 · see citing works

Cloud-Based Data Analytics for Healthcare 5.0

Kavitha, K., & Kumuthini, C. (2023) · Advances in healthcare information systems and administration book series · doi:10.4018/979-8-3693-2639-8.ch004 · Cited by 3 · see citing works

Big data analytics applied to health services: a literature review

Gomes, M. A. S., da Silva, V. L., Kovaleski, J. L., & Pagani, R. (2021) · Exacta · doi:10.5585/exactaep.2021.17297 · Cited by 3 · see citing works

Deep Convolutional Neural Network Feed Forward and Back Prop a gation (DCNN F BP) Algorithm f or Predicting Heart Disease u sing Internet o f Things

Saranya, N., & Priya, S. K. (2021) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.a3212.1011121 · Cited by 3 · see citing works

An Efficient Ensemble Model for Various Scale Medical Data

Elzeheiry, H. A., Barakat, S., & Rezk, A. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.027345 · Cited by 2 · see citing works

HealthCare Data Analytics: A Machine Learning-Based Perspective

Bharate, M., & Panicker, S. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-19-2069-1_24 · Cited by 2 · see citing works

From Big Data to Big Insights: A Synthesis of Real-World Applications of Big Data Analytics

Raisinghani, M. S., Idemudia, E. C., & Fen, W. (2023) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-031-40956-1_11 · Cited by 2 · see citing works

Big Data-Powered IoT Architectures for Smart Healthcare: A Comprehensive Review of Big Data Scalable Analytics, Fog Computing, and IoT Intelligent Healthcare Ecosystems

Das, A., Mondal, H., Chowdhury, T. A., Nag, A., & Bosu, P. (2025) · Springer eBooks · doi:10.1007/978-3-031-94386-7_9 · Cited by 1 · see citing works

AI-integrated clinical decision support systems for precision medicine in real-world healthcare

Khakpaki, A., javid, S. A., Farshbaf‐Khalili, A., & Sepehri, H. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01518-3 · Cited by 1 · see citing works

Harnessing Machine Learning and Big Data Analytics for Real-World Applications: A Comprehensive Survey

Seddik, S., Routaib, H., & Haddadi, A. E. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-90321-3_60 · Cited by 1 · see citing works

Dynamic Patient Categorization Based on Medical Records Using Fuzzy C-Means Clustering Technique

Wati, D. F., Renaldi, F., & Santikarama, I. (2023) · International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) · doi:10.1109/iccosite57641.2023.10127798 · Cited by 1 · see citing works

Dependable Mobile Federated Learning Classifications Focused for Mobile Intelligent Source Distribution System in Big Data Analytics using Artificial Internet of Things

Govindaram, A., Jegatheesan, A., & Baburaj, E. (2023) · International Conference on Science Technology Engineering and Mathematics (ICONSTEM) · doi:10.1109/iconstem56934.2023.10142688 · Cited by 1 · see citing works

Efficient Data Searching and Management with Search Desk: A Customizable Search Engine for Accurate and Timely Results

Kumar, J. N. V. R. S., Yakkala, P., Pasupuleti, S., Pagolu, P., Potharlanka, S. M. C., & Pittu, M. (2023) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt56998.2023.10307516 · Cited by 1 · see citing works

Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data

Knott, C. E., Gomori, S., Ngyuen, M., Pedrazzani, S. D., Sattaluri, S., Mierzwa, F. J., & Chantala, K. (2021) · EPJ Data Science · doi:10.1140/epjds/s13688-021-00264-z · Cited by 1 · see citing works

Internet of Things and Big Data Analytics for Smart Healthcare

Kumar, K. S., Prakash, P. G. O., Balaji, N. A., & Damaševičius, R. (2022) · doi:10.1002/9781119792550.ch7 · Cited by 1 · see citing works

Big Data Analytics and Visualization for Food Health Status Determination Using Bigmart Data

Hirve, S. A., & H., P. R. C. (2019) · Advances in data mining and database management book series · doi:10.4018/978-1-5225-9750-6.ch011

A Detailed Study on Implication of Big Data, Machine Learning and Cloud Computing in Healthcare Domain

Abirami, L., & Karthikeyan, J. (2021) · Learning and analytics in intelligent systems · doi:10.1007/978-3-030-65407-8_26

Data Optimization using Apache Flink

Vikas, S., & Thimmaraju, S. N. (2019) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.b3081.129219

Intelligent Big Data Analytics in Health

Bayrak, E. A., & Kirci, P. (2021) · IGI Global eBooks · doi:10.4018/978-1-6684-3662-2.ch081

Introduction to image-assisted disease screening

Dey, N., & Rajinikanth, V. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-823401-3.00001-8

Big Data Analytics and Visualization for Food Health Status Determination Using Bigmart Data

Hirve, S. A., & H., P. R. C. (2021) · IGI Global eBooks · doi:10.4018/978-1-6684-3662-2.ch025

Big Data in healthcare from a sex and gender perspective

Subirats, L., & Piella, G. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821392-6.00007-8

Development of Intelligent Healthcare Sytems Through Digital Transformation and Operations Research Modeling

Dural‐Selcuk, G. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-031-16598-6_13

Future Expectations About Big Data Analytics

Durugkar, S. R. (2024) · Advances in business information systems and analytics book series · doi:10.4018/979-8-3693-0413-6.ch019

Pengaruh Teknologi Big Data terhadap Financial Performance dan Competitive Advantage Studi pada Perusahaan Go Public di Indonesia Sektor Perbankan

Rahardja, A. S., & Hariyanto, W. (2024) · Innovative Technologica Methodical Research Journal · doi:10.47134/innovative.v2i2.24

Asthma Risk Prediction By Machine Learning Using IoT and Web App

(2024) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets48941

Data-driven models, techniques, and design principles for combatting healthcare fraud

Thornton, D. (2024) · doi:10.3990/1.9789036560160

A Survey on Big Data in Healthcare Applications

Ambigavathi, M., & Sridharan, D. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-8618-3_77 · Cited by 9 · see citing works

Impact of Big Data Analysis on HealthPreprint

Rosário, A. T., & Dias, J. C. (2022) · Preprints.org · doi:10.20944/preprints202203.0407.v1 · Cited by 1 · see citing works

Healthcare analytics in big data: current trends and prospects

Talukdar, U. (2022) · International Journal of Electronic Healthcare · doi:10.1504/ijeh.2022.124489

Big data analytics enhanced healthcare systems: a review

Shafqat, S., Kishwer, S., Rasool, R. U., Qadir, J., Amjad, T., & Ahmad, H. F. (2018) · The Journal of Supercomputing · doi:10.1007/s11227-017-2222-4 · Cited by 149 · see citing works

Big Data Analytics for Big Medical Data—Tools Applications and Challenges

Banu, A., Ameen, A., & Begum, Z. (2024) · Advanced technologies and societal change · doi:10.1007/978-981-97-3312-5_1