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This paper is in the following e-collection/theme issue:

Natural Language Processing (1311) Electronic Health Records (1753) Machine Learning (3268)

Published on in Vol 8, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14971, first published .
Medical equipment including stethoscope, syringe, and laptop with green cross

Generating Medical Assessments Using a Neural Network Model: Algorithm Development and Validation

Generating Medical Assessments Using a Neural Network Model: Algorithm Development and Validation

Authors of this article:

Baotian Hu1 Author Orcid Image ;   Adarsha Bajracharya2 Author Orcid Image ;   Hong Yu1, 3, 4 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Hayes C, Cucciare M, Martin B, Hudson T, Bush K, Lo-Ciganic W, Yu H, Charron E, Gordon A. Using Data Science to Improve Outcomes for Persons with Opioid use Disorder. Substance Abuse 2022;43(1):956 View
  2. Shen Y, Yu J, Zhou J, Hu G. Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review. Journal of Medical Internet Research 2025;27:e59024 View
  3. Magzoub M, Zafar I, Munshi F, Shersad F. Ten tips to harnessing generative AI for high-quality MCQS in medical education assessment. Medical Education Online 2025;30(1) View

Books/Policy Documents

  1. Del Fiol G, Yu H, Cimino J. Clinical Decision Support and Beyond. View
  2. Tang X, Filonczuk A, Zhang X, Cheng Y. Handbook of Generative AI in Education. View