A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians
Osaka Metropolitan University · Kobe University · +6 more institutions
Abstract
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…
Citation impact
- FWCI
- 53.56
- Percentile
- 100%
- References
- 120
Authors
8Topics & keywords
- Meta-analysis
- Generative grammar
- Reliability (semiconductor)
- Diagnostic accuracy
- Systematic review
- Artificial intelligence
- Diagnostic test
- Computer science