Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28946, first published .
Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study

Journals

  1. Zhao Y, Cao L, Zhao Y, Wang F, Xie L, Xing H, Wang Q. Medical record data-enabled machine learning can enhance prediction of left atrial appendage thrombosis in nonvalvular atrial fibrillation. Thrombosis Research 2023;223:174 View
  2. Li S, Deng L, Zhang X, Chen L, Yang T, Qi Y, Jiang T. Deep Phenotyping of Chinese Electronic Health Records by Recognizing Linguistic Patterns of Phenotypic Narratives With a Sequence Motif Discovery Tool: Algorithm Development and Validation. Journal of Medical Internet Research 2022;24(6):e37213 View
  3. Shipley E, Joddrell M, Lip G, Zheng Y. Bridging the Gap Between Artificial Intelligence Research and Clinical Practice in Cardiovascular Science: What the Clinician Needs to Know. Arrhythmia & Electrophysiology Review 2022;11 View
  4. Chiavi D, Haag C, Chan A, Kamm C, Sieber C, Stanikić M, Rodgers S, Pot C, Kesselring J, Salmen A, Rapold I, Calabrese P, Manjaly Z, Gobbi C, Zecca C, Walther S, Stegmayer K, Hoepner R, Puhan M, von Wyl V. The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing. JMIR Medical Informatics 2022;10(11):e37945 View
  5. Jaques-Albuquerque L, dos Anjos-Martins E, Torres-Nunes L, Valério-Penha A, Coelho-Oliveira A, da Silva Sarandy V, Reis-Silva A, Seixas A, Bernardo-Filho M, Taiar R, de Sá-Caputo D. Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review. Diagnostics 2023;13(8):1499 View
  6. Harris J. An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity. JAMA 2023;330(9):801 View
  7. De Rosario H, Pitarch-Corresa S, Pedrosa I, Vidal-Pedrós M, de Otto-López B, García-Mieres H, Álvarez-Rodríguez L. Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review. JMIR Medical Informatics 2023;11:e48693 View
  8. Liang J, He Y, Xie J, Fan X, Liu Y, Wen Q, Shen D, Xu J, Gu S, Lei J. Mining electronic health records using artificial intelligence: Bibliometric and content analyses for current research status and product conversion. Journal of Biomedical Informatics 2023;146:104480 View
  9. Skuban-Eiseler T, Orzechowski M, Denkinger M, Kocar T, Leinert C, Steger F. Artificial Intelligence–Based Clinical Decision Support Systems in Geriatrics: An Ethical Analysis. Journal of the American Medical Directors Association 2023;24(9):1271 View
  10. Laursen M, Pedersen J, Hansen R, Savarimuthu T, Lynggaard R, Vinholt P. Doctors Identify Hemorrhage Better during Chart Review when Assisted by Artificial Intelligence. Applied Clinical Informatics 2023;14(04):743 View
  11. Schopow N, Osterhoff G, Baur D. Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review. JMIR Medical Informatics 2023;11:e48933 View
  12. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  13. Guo R, Tian X, Bazoukis G, Tse G, Hong S, Chen K, Liu T. Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia. Pacing and Clinical Electrophysiology 2024;47(6):789 View
  14. Franklin G, Stephens R, Piracha M, Tiosano S, Lehouillier F, Koppel R, Elkin P. The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective. Life 2024;14(6):652 View
  15. Sun Y, Cosgun O, Sharman R, Mulgund P, Delen D. A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide. Decision Analytics Journal 2024;12:100504 View
  16. Song X, Wang J, He F, Yin W, Ma W, Wu J. Stroke Diagnosis and Prediction Tool Using ChatGLM: Development and Validation Study. Journal of Medical Internet Research 2025;27:e67010 View
  17. Raj A, Yadav T, Patil S, Kalra A, Sardana S, Nirbhavane P. Counterfeit medicine: a major public health concern and effective remedies for combatting the crisis. Discover Pharmaceutical Sciences 2025;1(1) View
  18. Remaki A, Ung J, Pages P, Wajsburt P, Liu E, Faure G, Petit-Jean T, Tannier X, Gérardin C. Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study. JMIR Medical Informatics 2025;13:e68704 View
  19. Amiri Z, Taghavirashidizadeh A, Khorrami P. AI-Driven Decision-Making in Healthcare Information Systems: A Comprehensive Review. Journal of Systems and Software 2025:112470 View
  20. Elkin P, Mehta G, LeHouillier F, Resnick M, Mullin S, Tomlin C, Resendez S, Liu J, Nebeker J, Brown S. Semantic Clinical Artificial Intelligence vs Native Large Language Model Performance on the USMLE. JAMA Network Open 2025;8(4):e256359 View
  21. Resnick M, Hitt J, McCray W, Hall K, LeHouillier F, Brown S, Campbell K, Montella D, Nebeker J, Elkin P. Semantic Relations: Extending SNOMED CT and Solor. Applied Clinical Informatics 2025;16(04):1263 View
  22. Elkin P, Lindsell C, Facelli J, Desai M, Weng C, Spratt H, Messinger S, Waitman L, Hairston J, O’Hara R, Meinzen-Derr J. Data science and artificial intelligence in biology, health, and healthcare. Journal of Clinical and Translational Science 2025;9(1) View
  23. Chalati M, Shirvankar C, Gore G, Sharma A, Abbasgholizadeh-Rahimi S, Al-Jumeily OBE D. Are Machine Learning methods effective in detecting undiagnosed atrial fibrillation in primary care settings using electronic health records? A systematic review. PLOS Digital Health 2025;4(10):e0001009 View
  24. Chen S, Huang W, Xu Y, Yang J. Reframing EHR Policy in China: Towards Balanced Implementation and Ethical Foundations. Journal of Evaluation in Clinical Practice 2025;31(7) View
  25. Zhang H, Geng X, Zhang Y, Du Y, Li D. A novel methodological framework for evaluating and optimizing PSS solutions based on user reviews and intelligent technologies. Advanced Engineering Informatics 2026;69:103948 View
  26. Guzik A, Fraser J, Southerland A, Vagal A, Tsai J, Dumitrascu O, Nystrom K, Martinez Johnson M, Hess D, Jayaraman M. Creating Virtual Stroke Networks: Current and Future Role of Artificial Intelligence, Mobile Imaging Applications, and Telehealth in Triage and Treatment of Acute Ischemic Stroke: A Scientific Statement From the American Heart Association. Stroke 2025 View

Books/Policy Documents

  1. Burger L, van Vuuren J. Dynamics of Information Systems. View