ArticleJournal of multidisciplinary healthcare2023
Are Different Versions of ChatGPT's Ability Comparable to the Clinical Diagnosis Presented in Case Reports? A Descriptive Study.
Article in Journal of multidisciplinary healthcare, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Exploring AI's Potential in Papilledema Diagnosis to Support Dermatological Treatment Decisions in Rural Healthcare.Diagnostics (Basel, Switzerland) · 2025Article
- The Role of ChatGPT in Dermatology Diagnostics.Diagnostics (Basel, Switzerland) · 2025Review
- Areas of research focus and trends in the research on the application of AIGC in healthcare.Journal of health, population, and nutrition · 2025Article
- Large Language Models in Medical Diagnostics: Scoping Review With Bibliometric Analysis.Journal of medical Internet research · 2025Article
- Assessing Information Provided by ChatGPT: Heart Failure Versus Patent Ductus Arteriosus.Cureus · 2025Article
- Using ChatGPT to assist in judging the indications for emergency ultrasound: an innovative exploration of optimizing medical resource allocation.Frontiers in medicine · 2025Article
- Qualitative metrics from the biomedical literature for evaluating large language models in clinical decision-making: a narrative review.BMC medical informatics and decision making · 2024Review
- The Application of ChatGPT in Medicine: A Scoping Review and Bibliometric Analysis.Journal of multidisciplinary healthcare · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: ChatGPT, an advanced language model developed by OpenAI, holds the opportunity to bring about a transformation in the processing of clinical decision-making within the realm of medicine. Despite the growing popularity of research related on ChatGPT, there is a paucity of research assessing its appropriateness for clinical decision support. Our study delved into ChatGPT's ability to respond in accordance with the diagnoses found in case reports, with the intention of serving as a reference for clinical decision-making. Methods: We included 147 case reports from the Chinese Medical Association Journal Database that generated primary and secondary diagnoses covering various diseases. Each question was independently posed three times to both GPT-3.5 and GPT-4.0, respectively. The results were analyzed regarding ChatGPT's mean scores and accuracy types. Results: GPT-4.0 displayed moderate accuracy in primary diagnoses. With the increasing number of input, a corresponding enhancement in the accuracy of ChatGPT's outputs became evident. Notably, autoimmune diseases comprised the largest proportion of case reports, and the mean score for primary diagnosis exhibited statistically significant differences in autoimmune diseases. Conclusion: Our finding suggested that the potential practicality in utilizing ChatGPT for clinical decision-making. To enhance the accuracy of ChatGPT, it is necessary to integrate it with the existing electronic health record system in the future.
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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.