Published on in Vol 2, No 1 (2014): Jan-Jun

Big Data and Clinicians: A Review on the State of the Science

Big Data and Clinicians: A Review on the State of the Science

Big Data and Clinicians: A Review on the State of the Science

Authors of this article:

Weiqi Wang1 ;   Eswar Krishnan1

Journals

  1. Mbagwu M, French D, Gill M, Mitchell C, Jackson K, Kho A, Bryar P. Creation of an Accurate Algorithm to Detect Snellen Best Documented Visual Acuity from Ophthalmology Electronic Health Record Notes. JMIR Medical Informatics 2016;4(2):e14 View
  2. Bink A, Benner J, Reinhardt J, De Vere-Tyndall A, Stieltjes B, Hainc N, Stippich C. Structured Reporting in Neuroradiology: Intracranial Tumors. Frontiers in Neurology 2018;9 View
  3. Sutherland S, Chawla L, Kane-Gill S, Hsu R, Kramer A, Goldstein S, Kellum J, Ronco C, Bagshaw S. Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15thADQI Consensus Conference. Canadian Journal of Kidney Health and Disease 2016;3:99 View
  4. Friedman S, Friedman Y. The future of hepatology: Embrace change. Clinical Liver Disease 2015;5(6):127 View
  5. Osborne T, Clark R, Blackowiak J, Williamson P, Werb S, Strong B. Efficiency Analysis of an Interoperable Healthcare Operations Platform. Journal of Medical Systems 2017;41(4) View
  6. Rabey M, Smith A, Kent P, Beales D, Slater H, O’Sullivan P. Chronic low back pain is highly individualised: patterns of classification across three unidimensional subgrouping analyses. Scandinavian Journal of Pain 2019;19(4):743 View
  7. Iwashyna T, Liu V. What’s So Different about Big Data?. A Primer for Clinicians Trained to Think Epidemiologically. Annals of the American Thoracic Society 2014;11(7):1130 View
  8. Azadmanjir Z, Safdari R, Ghazisaeidi M. From Self-care for Healthy People to Self-management for Cancer Patients with Cancer Portals. Asian Pacific Journal of Cancer Prevention 2015;16(4):1321 View
  9. Caldieraro M. The future of psychiatric research. Trends in Psychiatry and Psychotherapy 2016;38(4):185 View
  10. Parra Calderón C. Big data en sanidad en España: la oportunidad de una estrategia nacional. Gaceta Sanitaria 2016;30(1):63 View
  11. Nazir S, Khan S, Khan H, Ali S, Garcia-Magarino I, Atan R, Nawaz M. A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming. IEEE Access 2020;8:95714 View
  12. Huang C, Syed-Abdul S, Jian W, Iqbal U, Nguyen P, Lee P, Lin S, Hsu W, Wu M, Wang C, Ma K, Li Y. A novel tool for visualizing chronic kidney disease associated polymorbidity: a 13-year cohort study in Taiwan. Journal of the American Medical Informatics Association 2015;22(2):290 View
  13. Schaarup C, Pape-Haugaard L, Hejlesen O. Models Used in Clinical Decision Support Systems Supporting Healthcare Professionals Treating Chronic Wounds: Systematic Literature Review. JMIR Diabetes 2018;3(2):e11 View
  14. Nazir S, Nawaz M, Adnan A, Shahzad S, Asadi S. Big Data Features, Applications, and Analytics in Cardiology—A Systematic Literature Review. IEEE Access 2019;7:143742 View
  15. Luo J, Wu M, Gopukumar D, Zhao Y. Big Data Application in Biomedical Research and Health Care: A Literature Review. Biomedical Informatics Insights 2016;8:BII.S31559 View
  16. Dion M, Diouf N, Robitaille H, Turcotte S, Adekpedjou R, Labrecque M, Cauchon M, Légaré F. Teaching Shared Decision Making to Family Medicine Residents: A Descriptive Study of a Web-Based Tutorial. JMIR Medical Education 2016;2(2):e17 View
  17. Monteith S, Glenn T, Geddes J, Bauer M. Big data are coming to psychiatry: a general introduction. International Journal of Bipolar Disorders 2015;3(1) View
  18. van Santen J, Kautsar S, Medema M, Linington R. Microbial natural product databases: moving forward in the multi-omics era. Natural Product Reports 2021;38(1):264 View
  19. Deserno T, Marx N. Computational Electrocardiography: Revisiting Holter ECG Monitoring. Methods of Information in Medicine 2016;55(04):305 View
  20. Rana A, Mugavero M. How Big Data Science Can Improve Linkage and Retention in Care. Infectious Disease Clinics of North America 2019;33(3):807 View
  21. Shachar N, Mitelpunkt A, Kozlovski T, Galili T, Frostig T, Brill B, Marcus-Kalish M, Benjamini Y. The Importance of Nonlinear Transformations Use in Medical Data Analysis. JMIR Medical Informatics 2018;6(2):e27 View
  22. McDermott S, Turk M. What are the implications of the big data paradigm shift for disability and health?. Disability and Health Journal 2015;8(3):303 View
  23. Guha S, Kumar S. Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap. Production and Operations Management 2018;27(9):1724 View
  24. Alsenan S, Al-Turaiki I, Hafez A. A Recurrent Neural Network Model to Predict Blood-Brain Barrier Permeability. Computational Biology and Chemistry 2020:107377 View
  25. Mostert M, Bredenoord A, Biesaart M, van Delden J. Big Data in medical research and EU data protection law: challenges to the consent or anonymise approach. European Journal of Human Genetics 2016;24(7):956 View
  26. Dallmann A, Mian P, den Anker J, Allegaert K. Clinical Pharmacokinetic Studies in Pregnant Women and the Relevance of Pharmacometric Tools. Current Pharmaceutical Design 2019;25(5):483 View
  27. Davison S. Personalized Approach and Precision Medicine in Supportive and End-of-Life Care for Patients With Advanced and End-Stage Kidney Disease. Seminars in Nephrology 2018;38(4):336 View
  28. Fredriksson C. Big data creating new knowledge as support in decision-making: practical examples of big data use and consequences of using big data as decision support. Journal of Decision Systems 2018;27(1):1 View
  29. Janke A, Overbeek D, Kocher K, Levy P. Exploring the Potential of Predictive Analytics and Big Data in Emergency Care. Annals of Emergency Medicine 2016;67(2):227 View
  30. Kortüm K, Müller M, Hirneiß C, Babenko A, Nasseh D, Kern C, Kampik A, Priglinger S, Kreutzer T. „Smart eye data“. Der Ophthalmologe 2016;113(6):469 View
  31. Westra B, Sylvia M, Weinfurter E, Pruinelli L, Park J, Dodd D, Keenan G, Senk P, Richesson R, Baukner V, Cruz C, Gao G, Whittenburg L, Delaney C. Big data science: A literature review of nursing research exemplars. Nursing Outlook 2017;65(5):549 View
  32. Hackl W, Ammenwerth E. SPIRIT: Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data. Methods of Information in Medicine 2016;55(02):114 View
  33. Strotbaum V, Pobiruchin M, Schreiweis B, Wiesner M, Strahwald B. Your data is gold – Data donation for better healthcare?. it - Information Technology 2019;61(5-6):219 View
  34. Treder M, Gaber A, Rudloff B, Eter N. Real-Life-Daten-Analyse der Therapiequalität bei Patienten mit exsudativer altersabhängiger Makuladegeneration (AMD) und venösen Gefäßverschlüssen an einer deutschen Universitätsaugenklinik. Der Ophthalmologe 2019;116(6):553 View
  35. Chen Y, Wang Z, Yuan G, Huang L. An overview of online based platforms for sharing and analyzing electrophysiology data from big data perspective. WIREs Data Mining and Knowledge Discovery 2017;7(4) View
  36. Fang Z, Fan X, Chen G. A study on specialist or special disease clinics based on big data. Frontiers of Medicine 2014;8(3):376 View
  37. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
  38. Schee genannt Halfmann S, Evangelatos N, Schröder-Bäck P, Brand A. European Healthcare Systems Readiness to Shift from ‘One-Size Fits All’ to Personalized Medicine. Personalized Medicine 2017;14(1):63 View
  39. Modi N, Ashby D, Battersby C, Brocklehurst P, Chivers Z, Costeloe K, Draper E, Foster V, Kemp J, Majeed A, Murray J, Petrou S, Rogers K, Santhakumaran S, Saxena S, Statnikov Y, Wong H, Young A. Developing routinely recorded clinical data from electronic patient records as a national resource to improve neonatal health care: the Medicines for Neonates research programme. Programme Grants for Applied Research 2019;7(6):1 View
  40. Silverio A, Cavallo P, De Rosa R, Galasso G. Big Health Data and Cardiovascular Diseases: A Challenge for Research, an Opportunity for Clinical Care. Frontiers in Medicine 2019;6 View
  41. Oyinlola J, Campbell J, Kousoulis A. Is real world evidence influencing practice? A systematic review of CPRD research in NICE guidances. BMC Health Services Research 2016;16(1) View
  42. Zhu V, Tuggle C, Au A. Promise and Limitations of Big Data Research in Plastic Surgery. Annals of Plastic Surgery 2016;76(4):453 View
  43. Danso S, Job D, Gonzalez D, Dickie D, Palmer J, Ure J, Bath P, Sandercock P, Wardlaw J. Developing an Integrated Image Bank and Metadata for Large-scale Research in Cerebrovascular Disease: Our Experience from the Stroke Image Bank Project. Frontiers in ICT 2016;3 View
  44. Ali R, Hussain J, Siddiqi M, Hussain M, Lee S. H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus. Sensors 2015;15(7):15921 View
  45. Rodeghero J, Cook C. The use of big data in manual physiotherapy. Manual Therapy 2014;19(6):509 View
  46. Balla A, Batista Rodríguez G, Corradetti S, Balagué C, Fernández-Ananín S, Targarona E. Outcomes after bariatric surgery according to large databases: a systematic review. Langenbeck's Archives of Surgery 2017;402(6):885 View
  47. MacRae J, Darlow B, McBain L, Jones O, Stubbe M, Turner N, Dowell A. Accessing primary care Big Data: the development of a software algorithm to explore the rich content of consultation records. BMJ Open 2015;5(8):e008160 View
  48. Cirillo D, Catuara-Solarz S, Morey C, Guney E, Subirats L, Mellino S, Gigante A, Valencia A, Rementeria M, Chadha A, Mavridis N. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. npj Digital Medicine 2020;3(1) View
  49. Brennan P, Bakken S. Nursing Needs Big Data and Big Data Needs Nursing. Journal of Nursing Scholarship 2015;47(5):477 View
  50. Agoston D, Langford D. Big Data in traumatic brain injury; promise and challenges. Concussion 2017;2(4):CNC44 View
  51. Lee C, Yoon H. Medical big data: promise and challenges. Kidney Research and Clinical Practice 2017;36(1):3 View
  52. Carrington J, Love R. Development of an Innovative Tool to Appraise Big Data for Best Evidence. Worldviews on Evidence-Based Nursing 2020;17(4):269 View
  53. Woldu S, Raj G. The surgeon–scientist — a dying breed?. Nature Reviews Urology 2016;13(12):698 View
  54. Yang J, Li Y, Liu Q, Li L, Feng A, Wang T, Zheng S, Xu A, Lyu J. Brief introduction of medical database and data mining technology in big data era. Journal of Evidence-Based Medicine 2020;13(1):57 View
  55. Dórea F, Revie C. Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making. Frontiers in Veterinary Science 2021;8 View
  56. Thakkar I, Massardo T, Pereira J, Quintana J, Risco L, Saez C, Corral S, Villa C, Spuler J, Olivares N, Valenzuela G, Castro G, Riedel B, Vicentini D, Muñoz D, Lastra R, Rodriguez-Fernandez M. Identification of Statin’s Action in a Small Cohort of Patients with Major Depression. Applied Sciences 2021;11(6):2827 View
  57. Sung L, Corbin C, Steinberg E, Vettese E, Campigotto A, Lecce L, Tomlinson G, Shah N. Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments. BMC Cancer 2020;20(1) View
  58. Parmar C, Barry J, Hosny A, Quackenbush J, Aerts H. Data Analysis Strategies in Medical Imaging. Clinical Cancer Research 2018;24(15):3492 View
  59. Hur C, Wi J, Kim Y. Facilitating the Development of Deep Learning Models with Visual Analytics for Electronic Health Records. International Journal of Environmental Research and Public Health 2020;17(22):8303 View
  60. Muller S, Kalkman S, van Thiel G, Mostert M, van Delden J. The social licence for data-intensive health research: towards co-creation, public value and trust. BMC Medical Ethics 2021;22(1) View
  61. Ning S, Li N, Barty R, Arnold D, Heddle N. Database‐driven research and big data analytic approaches in transfusion medicine. Transfusion 2022;62(7):1427 View
  62. Sun A, Johnson D. Characterization of Traumatic Injury During the Early COVID-19 Pandemic: Results From a National Healthcare Database. Cureus 2022 View
  63. Soenksen L, Ma Y, Zeng C, Boussioux L, Villalobos Carballo K, Na L, Wiberg H, Li M, Fuentes I, Bertsimas D. Integrated multimodal artificial intelligence framework for healthcare applications. npj Digital Medicine 2022;5(1) View
  64. Alexander N, Aftandilian C, Guo L, Plenert E, Posada J, Fries J, Fleming S, Johnson A, Shah N, Sung L. Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study. JMIR Medical Informatics 2022;10(11):e40039 View
  65. Wang M, Li S, Zheng T, Li N, Shi Q, Zhuo X, Ding R, Huang Y. Big Data Health Care Platform With Multisource Heterogeneous Data Integration and Massive High-Dimensional Data Governance for Large Hospitals: Design, Development, and Application. JMIR Medical Informatics 2022;10(4):e36481 View
  66. Vesoulis Z, Husain A, Cole F. Improving child health through Big Data and data science. Pediatric Research 2023;93(2):342 View
  67. Khan I, Javaid M. Big Data Applications in Medical Field: A Literature Review. Journal of Industrial Integration and Management 2021;06(01):53 View
  68. Pablo R, Roberto D, Victor S, Isabel G, Paul C, Elizabeth O. Big data in the healthcare system: a synergy with artificial intelligence and blockchain technology. Journal of Integrative Bioinformatics 2022;19(1) View
  69. Siripurapu S, Darimireddy N, Chehri A, Sridhar B, Paramkusam A. Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-I (AI, Big Data, Block Chain, Open-Source Technologies, and Cloud Computing). Electronics 2023;12(3):750 View
  70. Li J, Li Z, Wang Y, Lin H, Wu B. TLSEA: a tool for lncRNA set enrichment analysis based on multi-source heterogeneous information fusion. Frontiers in Genetics 2023;14 View
  71. Annis A, Reaves C, Sender J, Bumpus S. Health-Related Data Sources Accessible to Health Researchers From the US Government: Mapping Review. Journal of Medical Internet Research 2023;25:e43802 View
  72. Shim S, Lee J, Kim J. Medical Application of Big Data: Between Systematic Review and Randomized Controlled Trials. Applied Sciences 2023;13(16):9260 View
  73. Lu S, Yang J, Gu Y, He D, Wu H, Sun W, Xu D, Li C, Guo C. Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors. ACS Sensors 2024;9(3):1134 View
  74. Li J, Ma X, Lin H, Zhao S, Li B, Huang Y. MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion. Frontiers in Genetics 2024;15 View

Books/Policy Documents

  1. Papadopoulou P, Lytras M, Marouli C. Applying Big Data Analytics in Bioinformatics and Medicine. View
  2. Martinez-Mosquera D, Luján-Mora S, Montoya L. L, Reyes Ch. R, Paredes Calderón M. Advances in Emerging Trends and Technologies. View
  3. Papadopoulou P, Lytras M, Marouli C. Biotechnology. View
  4. Gaitanou P, Garoufallou E, Balatsoukas P. Metadata and Semantics Research. View
  5. Nicholls S, Langan S, Benchimol E. The Ethics of Biomedical Big Data. View
  6. Cinaroglu S. Analytics, Operations, and Strategic Decision Making in the Public Sector. View
  7. Papadopoulou P, Chui K, Daniela L, Lytras M. Cognitive Computing in Technology-Enhanced Learning. View
  8. Tempini N, Leonelli S. Encyclopedia of Life Sciences. View
  9. Ortega M, Genero M, Piattini M. Model and Data Engineering. View
  10. Sharma N, Patil M, Shamkuwar M. Internet of Things in Biomedical Engineering. View
  11. Tekchandani S, Shah J, Singh A. Data Science and Intelligent Applications. View
  12. Hardy L, Bourne P. Big Data-Enabled Nursing. View
  13. A. R, V. T. K, A. S. Deep Neural Networks for Multimodal Imaging and Biomedical Applications. View
  14. Agoston D. Leveraging Biomedical and Healthcare Data. View
  15. Mathew P, Pillai A. Innovations in Bio-Inspired Computing and Applications. View
  16. Umar Otokiti A. Contemporary Topics in Patient Safety - Volume 1. View
  17. Cinaroglu S. Research Anthology on Public Health Services, Policies, and Education. View
  18. Varshney M, Bhushan B, Haque A. Multimedia Technologies in the Internet of Things Environment, Volume 3. View
  19. Subirats L, Piella G. Sex and Gender Bias in Technology and Artificial Intelligence. View
  20. Iyamu T, Mgudlwa S. Research Anthology on Big Data Analytics, Architectures, and Applications. View
  21. Khan Mamun M, Alouani A. Advances in Information and Communication. View
  22. Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. View