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A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians
Hirotaka Takita1, Daijiro Kabata2, Shannon L Walston1,3
1Department of Diagnostic and Interventional Radiology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.
None:
While generative artificial intelligence (AI) has shown potential in medical diagnostics, comprehensive evaluation of its diagnostic performance and comparison with physicians has not been extensively explored. We conducted a systematic review and meta-analysis of studies validating generative AI models for diagnostic tasks published between June 2018 and June 2024. Analysis of 83 studies revealed an overall diagnostic accuracy of 52.1%. No significant performance difference was found between AI models and physicians overall (p = 0.10) or non-expert physicians (p = 0.93). However, AI models performed significantly worse than expert physicians (p = 0.007). Several models demonstrated slightly higher performance compared to non-experts, although the differences were not significant. Generative AI demonstrates promising diagnostic capabilities with accuracy varying by model. Although it has not yet achieved expert-level reliability, these findings suggest potential for enhancing healthcare delivery and medical education when implemented with appropriate understanding of its limitations.
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