Med-Flamingo
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Stanford's Med-Flamingo is a multimodal medical model supporting in-context learning for few-shot medical visual QA.
Medical ICL: Supports in-context learning for medical visual QA, letting clinicians specialize the model via examples at inference time rather than fine-tuning.
Physician evaluation: Physician evaluators rate Med-Flamingo's responses up to 20% higher than baseline multimodal models - a significant clinical quality improvement.
Hallucination concerns: Authors transparently report occasional low-quality generations and hallucinations, a necessary caveat for medical deployment.
Clinical-deployment template: Sets a template for responsible medical VLM development - physician-in-the-loop evaluation alongside automatic metrics.
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