Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43014, first published .
Extracting Medical Information From Free-Text and Unstructured Patient-Generated Health Data Using Natural Language Processing Methods: Feasibility Study With Real-world Data

Extracting Medical Information From Free-Text and Unstructured Patient-Generated Health Data Using Natural Language Processing Methods: Feasibility Study With Real-world Data

Extracting Medical Information From Free-Text and Unstructured Patient-Generated Health Data Using Natural Language Processing Methods: Feasibility Study With Real-world Data

Journals

  1. Choi E, Leonard K, Jassal J, Levin A, Ramachandra V, Jones L. Artificial Intelligence in Facial Plastic Surgery: A Review of Current Applications, Future Applications, and Ethical Considerations. Facial Plastic Surgery 2023;39(05):454 View
  2. Stasevych M, Zvarych V. Innovative Robotic Technologies and Artificial Intelligence in Pharmacy and Medicine: Paving the Way for the Future of Health Care—A Review. Big Data and Cognitive Computing 2023;7(3):147 View
  3. Leviton A, Loddenkemper T. Design, implementation, and inferential issues associated with clinical trials that rely on data in electronic medical records: a narrative review. BMC Medical Research Methodology 2023;23(1) View
  4. Soto Jacome C, Segura Torres D, Fan J, Loor-Torres R, Duran M, Al Zahidy M, Cabezas E, Borras-Osorio M, Toro-Tobon D, Wu Y, Wu Y, Singh Ospina N, Brito J. Thyroid Ultrasound Appropriateness Identification Through Natural Language Processing of Electronic Health Records. Mayo Clinic Proceedings: Digital Health 2024;2(1):67 View

Books/Policy Documents

  1. Afşin Y, Taşkaya Temizel T. Persuasive Technology. View