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

Clinical Information and Decision Making (1656) Digital Health, Telehealth and e-Innovation in Clinical Settings (476) Clinical Informatics (1162) Decision Support for Health Professionals (1338) Machine Learning (1738) Generative Language Models Including ChatGPT (497) Artificial Intelligence (1740)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54616, first published .
AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation

AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation

AI-Driven Diagnostic Assistance in Medical Inquiry: Reinforcement Learning Algorithm Development and Validation

Authors of this article:

Xuan Zou1 Author Orcid Image ;   Weijie He2, 3, 4 Author Orcid Image ;   Yu Huang5 Author Orcid Image ;   Yi Ouyang5 Author Orcid Image ;   Zhen Zhang1 Author Orcid Image ;   Yu Wu1 Author Orcid Image ;   Yongsheng Wu1 Author Orcid Image ;   Lili Feng6 Author Orcid Image ;   Sheng Wu6 Author Orcid Image ;   Mengqi Yang7 Author Orcid Image ;   Xuyan Chen6 Author Orcid Image ;   Yefeng Zheng5 Author Orcid Image ;   Rui Jiang4, 8 Author Orcid Image ;   Ting Chen2, 3, 4 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics
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Nick Byrd Nick Byrd @byrd_nick

Can #machineLearning help new doctors? A model was trained on #electronicHealthRecords. On pediatric diagnoses, a simulated physician-ML collaboration outperformed a simulated physician, which outperformed the model. No benefit for emergency diagnoses? https://t.co/loqAH4hbV6 https://t.co/BirTKRSRKU

7:56 PM · Aug 28, 2024

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