
A new study evaluates the diagnostic accuracy of three leading generative multimodal AI models in interpreting CT images for lung cancer detection.
Key Details
- 1Three models compared: Gemini-pro-vision (Google), Claude-3-opus (Anthropic), and GPT-4-turbo (OpenAI).
- 2On 184 malignant lung cases, Gemini achieved highest single-image accuracy (>90%), followed by Claude-3-opus, GPT lowest (65.2%).
- 3Gemini's performance dropped to 58.5% with continuous CT slices, indicating challenges with spatial reasoning in imaging.
- 4Simplified text prompts improved diagnostic AUCs: Gemini (0.76), GPT (0.73), and Claude (0.69).
- 5Claude-3-opus showed superior consistency and lower variation in lesion feature analysis.
- 6External validation with TCGA and MIDRC datasets supported findings, especially with simplified prompt strategies.
Why It Matters

Source
EurekAlert
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