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

Formative Evaluation of Digital Health Interventions (3291) Artificial Intelligence (2186) Clinical Informatics (1348) Chatbots and Conversational Agents (754)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47814, first published .
Fine-Tuned Bidirectional Encoder Representations From Transformers Versus ChatGPT for Text-Based Outpatient Department Recommendation: Comparative Study

Fine-Tuned Bidirectional Encoder Representations From Transformers Versus ChatGPT for Text-Based Outpatient Department Recommendation: Comparative Study

Fine-Tuned Bidirectional Encoder Representations From Transformers Versus ChatGPT for Text-Based Outpatient Department Recommendation: Comparative Study

Authors of this article:

Eunbeen Jo1 Author Orcid Image ;   Hakje Yoo2, 3 Author Orcid Image ;   Jong-Ho Kim4, 5 Author Orcid Image ;   Young-Min Kim6 Author Orcid Image ;   Sanghoun Song7 Author Orcid Image ;   Hyung Joon Joo1, 4, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

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  3. Suri C, Ratre Y, Pande B, Bhaskar L, Verma H. Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine. World Journal of Gastroenterology 2026;32(1) View