AI RESEARCH
MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence
arXiv CS.CV
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ArXi:2603.27176v1 Announce Type: new Lesion detection, symptom tracking, and visual explainability are central to real-world medical image analysis, yet current medical Vision-Language Models (VLMs) still lack mechanisms that translate their broad knowledge into clinically actionable outputs. To bridge this gap, we present MEDIC-AD, a clinically oriented VLM that strengthens these three capabilities through a stage-wise framework. First, learnable anomaly-aware tokens encourage the model to focus on abnormal regions and build discriminative lesion centered representations.