Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44977, first published .
Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Journals

  1. Corbin C, Maclay R, Acharya A, Mony S, Punnathanam S, Thapa R, Kotecha N, Shah N, Chen J. DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record. Journal of the American Medical Informatics Association 2023;30(9):1532 View
  2. Fernando M, Abell B, Tyack Z, Donovan T, McPhail S, Naicker S. Using Theories, Models, and Frameworks to Inform Implementation Cycles of Computerized Clinical Decision Support Systems in Tertiary Health Care Settings: Scoping Review. Journal of Medical Internet Research 2023;25:e45163 View
  3. Li L, Yuan L, Yang K, Wu Y, Alafati S, Hua X, Wang Y, Yuan X. Comparison of the accuracy of 9 intraocular lens power calculation formulas after SMILE in Chinese myopic eyes. Scientific Reports 2023;13(1) View
  4. Gao J, Chen G, O’Rourke A, Caskey J, Carey K, Oguss M, Stey A, Dligach D, Miller T, Mayampurath A, Churpek M, Afshar M. Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models. Journal of the American Medical Informatics Association 2024;31(6):1291 View
  5. Pinsky M, Bedoya A, Bihorac A, Celi L, Churpek M, Economou-Zavlanos N, Elbers P, Saria S, Liu V, Lyons P, Shickel B, Toral P, Tscholl D, Clermont G. Use of artificial intelligence in critical care: opportunities and obstacles. Critical Care 2024;28(1) View
  6. Nilius H, Tsouka S, Nagler M, Masoodi M. Machine learning applications in precision medicine: Overcoming challenges and unlocking potential. TrAC Trends in Analytical Chemistry 2024;179:117872 View
  7. Mwogosi A. Revolutionizing primary health care in Tanzania: unravelling the contextual factors on electronic health record systems implementation for effective decision support. Journal of Science and Technology Policy Management 2024 View
  8. Eguia H, Sánchez-Bocanegra C, Vinciarelli F, Alvarez-Lopez F, Saigí-Rubió F. Clinical Decision Support and Natural Language Processing in Medicine: Systematic Literature Review. Journal of Medical Internet Research 2024;26:e55315 View
  9. Machado M, Marques J, Gualdani F, Dos Santos M, Lario F, De Araujo C, Oliveira F, Ensina L, Marcacini R, Moreira D. Evaluating large language models for anaphylaxis detection in clinical notes. Journal of Health Informatics 2024;16(Especial) View
  10. Coleman B, Corcoran K, Brandt C, Goulet J, Luther S, Lisi A. Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis. JMIR Medical Informatics 2025;13:e66466 View
  11. Afshar M, Resnik F, Joyce C, Oguss M, Dligach D, Burnside E, Sullivan A, Churpek M, Patterson B, Salisbury-Afshar E, Liao F, Goswami C, Brown R, Mundt M. Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults. Nature Medicine 2025;31(6):1863 View
  12. Liu H, Li Z, Song Z. Comprehensive lifecycle quality control of medical data - automated monitoring and feedback mechanisms based on artificial intelligence. Technology and Health Care 2025;33(5):2125 View
  13. Alon Y, Naimi E, Levin C, Videl H, Saban M. Leveraging natural language processing to elucidate real-world clinical decision-making paradigms: A proof of concept study. Journal of Biomedical Informatics 2025;166:104829 View
  14. 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
  15. Kotula C, Martin J, Carey K, Edelson D, Dligach D, Mayampurath A, Afshar M, Churpek M. Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study. Journal of Medical Internet Research 2025;27:e75340 View
  16. Chattaraj R, Chimalakonda S. NLP Libraries, Energy Consumption and Runtime: An Empirical Study. Proceedings of the ACM on Software Engineering 2025;2(FSE):2850 View
  17. Patel K, Connor A, Kodali S, Mobley C, Victor D, Hobeika M, Dib Y, Saharia A, Cheah Y, Simon C, Brombosz E, Moore L, Ghobrial R. From prediction to practice: a narrative review of recent artificial intelligence applications in liver transplantation. Artificial Intelligence Surgery 2025;5(2):298 View
  18. Thang C, Duffy C, Khattab S, Semenov Y. The Current State and Future Prospects for Artificial Intelligence in Dermatology. Dermatologic Clinics 2025 View

Books/Policy Documents

  1. Katebi M, Poshdar M, Babaeian Jelodar M, Zihayat Kermani M. CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. View
  2. Katebi M, Poshdar M, Babaeian Jelodar M, Zihayat Kermani M. CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. View
  3. Katebi M, Poshdar M, Babaeian Jelodar M, Zihayat Kermani M. CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. View