ArticleBMC research notes2025
The feasibility of using generative artificial intelligence for history taking in virtual patients.
Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large Language Model-Based Virtual Patient Systems for History-Taking in Medical Education: Comprehensive Systematic Review.JMIR medical informatics · 2026Pooled it
- Utilizing generative artificial intelligence to create simulated patient for history taking in gynecology.BMC medical education · 2026Trial
- Comparing AI chatbot simulation and peer role-play for OSCE preparation: a pilot randomized controlled trial.BMC medical education · 2025Trial
- AI-simulated clinical consultations: Assessing the potential of ChatGPT to support medical training.Archives of disease in childhood · 2026Article
- Safety-First Framework for AI-Enabled Anamnesis in Head and Neck Surgery: Evidence Synthesis from a Narrative Review.Journal of clinical medicine · 2026Review
- Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study.JMIR medical education · 2026Article
- Development and expert evaluation of a culturally adapted large language model for Malay clinical history-taking simulation: mixed methods study.Frontiers in medicine · 2026Article
- Can ChatGPT-5 educate the public about vasectomy?: a Google Trends-based expert panel assessment.Frontiers in digital health · 2026Article
- Embracing the Future of Medical Education With Large Language Model-Based Virtual Patients: Scoping Review.Journal of medical Internet research · 2025Article
- Advancing Toward P6 Medicine: Recommendations for Integrating Artificial Intelligence in Internal Medicine.Clinics and practice · 2025Article
- Psychiatry in the age of AI: transforming theory, practice, and medical education.Frontiers in public health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
objectiveThis study aimed to design and develop a virtual patient program using generative Artificial Intelligence (AI) technology, providing medical students opportunities to practice history-taking with a chatbot. We evaluated the feasibility of this approach by analyzing the quality of responses generated by the chatbot.
resultsFive expert reviewers participated in a pilot test, interacting with the chatbot to take the history of a patient presenting with a urinary problem using the Korean AI platform Naver HyperCLOVA X
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.