Published on in Vol 10, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38557, first published .
Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities

Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities

Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities

Journals

  1. Joyce C, Markossian T, Nikolaides J, Ramsey E, Thompson H, Rojas J, Sharma B, Dligach D, Oguss M, Cooper R, Afshar M. The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design. JMIR Research Protocols 2022;11(12):e42971 View
  2. Johns M, Meurers T, Wirth F, Haber A, Müller A, Halilovic M, Balzer F, Prasser F. Data Provenance in Biomedical Research: Scoping Review. Journal of Medical Internet Research 2023;25:e42289 View
  3. Tseng Y, Chen C, Chang C. lab: an R package for generating analysis-ready data from laboratory records. PeerJ Computer Science 2023;9:e1528 View
  4. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
  5. Kervezee L, Dashti H, Pilz L, Skarke C, Ruben M, Forger D. Using routinely collected clinical data for circadian medicine: A review of opportunities and challenges. PLOS Digital Health 2024;3(5):e0000511 View
  6. Naderian S, Rahmani R, Samad-Soltani T. A Natural Language Processing Framework for Detecting Adverse Drug Reactions in Clinical Structured Drug Reviews. International Journal of Drug Research in Clinics 2024;2:e9 View

Books/Policy Documents

  1. Maletzky A, Kaltenleithner S, Moser P, Giretzlehner M. Artificial Intelligence Applications and Innovations. View