Adaptive multimodal AI improves medical image retrieval, generation speed, and clinical auditing for radiology education

A multimodal AI education tool reached 38.83% top-1 retrieval recall across 65,419 images and 12.5x faster CPU synthesis; blinded radiologists saw only a small quality drop, and its LLM auditor correlated 0.805 with an expert radiologist.

• Design: extended MIRAGE multimodal retrieval/generation system with Auto-α adaptive weighting, LCM-LoRA accelerated synthesis, and Gemini 2.5 Flash clinical auditing.
• Primary retrieval result: 38.83% Top-1 recall over a 65,419-image ROCO gallery, outperforming nine fusion baselines; ablation attributed gain to learning the weight rather than query-adaptive weighting alone.
• LCM-LoRA cut CPU compute by 12.5x with blinded radiologist review indicating only a small drop in clinical quality; clinical auditor reached 0.805 Pearson correlation and corrected traditional CLIP score overestimation.

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