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

Foundation Models and Their Applications in AI (98) Clinical Informatics (2099) Clinical Information and Decision Making (3454) Natural Language Processing (1208) Ontologies, Classifications, and Coding (404) Diagnostic Tools in Mental Health (411) Computer-Aided Diagnosis (401) Generative Language Models Including ChatGPT (1372)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75030, first published .
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Aiding Large Language Models Using Clinical Scoresheets for Neurobehavioral Diagnostic Classification From Text: Algorithm Development and Validation

Aiding Large Language Models Using Clinical Scoresheets for Neurobehavioral Diagnostic Classification From Text: Algorithm Development and Validation

Authors of this article:

Kaiying Lin1 Author Orcid Image ;   Abdur Rasool2 Author Orcid Image ;   Saimourya Surabhi3 Author Orcid Image ;   Cezmi Mutlu3 Author Orcid Image ;   Haopeng Zhang2 Author Orcid Image ;   Dennis P Wall3 Author Orcid Image ;   Peter Washington4 Author Orcid Image
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Journals

  1. Yang S, Liu S, Ma Y, Gai B, Liu J, Wang L, Gao F, Zhou Z. Real-world performance of open-source large language models in diabetes diagnosis. Frontiers in Endocrinology 2026;17 View
  2. Sarma K, Hanss K, Halls A, Becker D, Glowinski A, Krystal A. Simulated Reasoning and Self-Verification for Psychiatric Diagnosis in Generalist Large Language Models: Comparative Evaluation. JMIR AI 2026;5:e83927 View