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Feasibility of Large Language Model-Based Standardized Virtual Patients to Support Clinical Decision-Making Training in Operative Dentistry: Mixed Methods Study.

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Title: Feasibility of Large Language Model-Based Standardized Virtual Patients to Support Clinical Decision-Making Training in Operative Dentistry: Mixed Methods Study.
Authors: BaHammam F; College of Dentistry, King Saud bin Abdulaziz University for Health Sciences, Prince Mutib Ibn Abdullah Ibn Abdulaziz Rd, Ar Rimayah, Riyadh, Saudi Arabia, 966 114295941.; King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.; Dental Services, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.
Source: JMIR formative research [JMIR Form Res] 2026 May 19; Vol. 10, pp. e91021. Date of Electronic Publication: 2026 May 19.
Publication Type: Journal Article
Journal Info: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101726394 Publication Model: Electronic Cited Medium: Internet ISSN: 2561-326X (Electronic) Linking ISSN: 2561326X NLM ISO Abbreviation: JMIR Form Res Subsets: MEDLINE
Database: MEDLINE Ultimate
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        Value: 10.2196/91021
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      – TitleFull: Feasibility of Large Language Model-Based Standardized Virtual Patients to Support Clinical Decision-Making Training in Operative Dentistry: Mixed Methods Study.
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              Text: 2026 May 19
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