ArticleJournal of evaluation in clinical practice2026
ChatGPT in Public Cardiovascular Healthcare: Accuracy, Limitations, and Implications.
Article in Journal of evaluation in clinical practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
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Who cites it
1 citing paper in PubMed.
- ChatGPT in Public Cardiovascular Healthcare: Accuracy, Limitations, and Implications.Journal of evaluation in clinical practice · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
introductionChatGPT is a cost-effective artificial intelligence (AI) tool designed to facilitate virtual interactions with humans, and its application in healthcare is expanding. However, research on ChatGPT's effectiveness in public healthcare, particularly for cardiac patients, is still limited. This study aims to evaluate ChatGPT's potential in managing cardiovascular health for patients with acute or chronic cardiac conditions.
methodsWe analyzed real medical records from 'The Cardiovascular Care' program, affiliated with a university outpatient clinic. ChatGPT's performance was evaluated in terms of its ability to analyze clinical cases, propose diagnoses, and recommend appropriate actions. We also assessed whether ChatGPT's accuracy and errors varied depending on disease severity, rarity, mortality risk, and urgency.
resultsWhen compared to physicians' records, ChatGPT provided correct responses in 43% of diagnostic hypotheses, 5% of recommended supplementary exams, and 10% of laboratory tests. It showed significant accuracy and discernment in diagnosing conditions influenced by factors such as severity, rarity, risk of death, and urgency. However, this discernment did not extend to recommendations for supplementary exams and laboratory tests. Interestingly, while ChatGPT's responses in these areas were often only partially accurate, they tended to be more detailed, sometimes unnecessarily so, than those provided by physicians. Diagnostic hypotheses from multiple models, including ChatGPT Health, DeepSeek, Gemini Pro, Perplexity AI, and ESC Chat, were also evaluated. Performance varied across models, with ChatGPT demonstrating the highest diagnostic accuracy among those assessed, despite still producing incorrect outputs.
conclusionAlthough ChatGPT demonstrates some diagnostic capability, its overall reliability remains questionable, with performance at times approaching random chance. Caution is advised when considering its use in clinical decision-making.
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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.