Evidence map›Paper›PMID 38084123›Full record

ArticleJournal of multidisciplinary healthcare2023

Are Different Versions of ChatGPT's Ability Comparable to the Clinical Diagnosis Presented in Case Reports? A Descriptive Study.

Jingfang Chen, Linlin Liu, Shujin Ruan, Mengjun Li, Chengliang Yin

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 30% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. The Role of ChatGPT in Dermatology Diagnostics.Diagnostics (Basel, Switzerland) · 2025
    Review
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Jingfang ChenFaculty of Medicine, Macau University of Science and Technology, Macau, People's Republic of China.ORCID 0000-0001-8389-7703
Linlin LiuHengyang Medical School, School of Nursing, University of South China, Hengyang, People's Republic of China.
Shujin RuanHengyang Medical School, School of Nursing, University of South China, Hengyang, People's Republic of China.
Mengjun LiHengyang Medical School, School of Nursing, University of South China, Hengyang, People's Republic of China.
Chengliang YinFaculty of Medicine, Macau University of Science and Technology, Macau, People's Republic of China.ORCID 0000-0001-8262-5749
Macau University of Science and Technology · MOUniversity of South China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligencecase reportsChatGPTclinical decision support systems

Identifiers

PMID38084123
PMCPMC10710805
OpenAlexW4389335502

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.