Fine-tuned MedGemma outperforms untuned GPT-4 in zero-shot medical image disease classification, achieving 80.37% versus 69.58% mean test accuracy with higher sensitivity for cancer and pneumonia.
A curated mammography data set for use in computer -aided detection and diagnosis research,
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MedGemma vs GPT-4: Open-Source and Proprietary Zero-shot Medical Disease Classification from Images
Fine-tuned MedGemma outperforms untuned GPT-4 in zero-shot medical image disease classification, achieving 80.37% versus 69.58% mean test accuracy with higher sensitivity for cancer and pneumonia.