
GenAI models demonstrate high accuracy and consistency in pathological grading and risk assessment for lung adenocarcinoma.
Key Details
- 1Study tested GPT-4o, Claude-3.5-Sonnet, and Gemini-1.5-Pro on 492 digitized slides from public and independent sources.
- 2Claude-3.5-Sonnet achieved 82.3% accuracy in lung adenocarcinoma grading, with strong repeatability.
- 3Models extracted 11 histological features and 4 clinical variables for comprehensive risk assessment.
- 4Diagnostic and prognostic tasks were completed in minutes, much faster than human experts.
- 5AI models reduced inter-observer variability and enabled objective, standardized analysis across multiple samples.
- 6GenAI models surfaced new significant prognostic factors including interstitial fibrosis and papillary patterns.
Why It Matters

Source
EurekAlert
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