Integrating general-purpose multimodal foundation models into medical applications

Determine effective methodologies to integrate general-purpose multimodal foundation models into medical applications and optimize these models for domain-specific semantics and diagnostic reasoning in clinical settings.

Background

The paper surveys recent progress in large multimodal foundation models such as Qwen2.5-VL, Qwen3-VL, and InternVL-3, noting their strong capabilities on general vision–language tasks. It also highlights growing interest in domain-specific medical multimodal models (e.g., Lingshu-32B) designed for medical image interpretation.

Despite this progress, the authors emphasize that translating general-purpose multimodal models to clinical domains remains challenging. Medical tasks require alignment with domain-specific semantics, safety, and diagnostic reasoning. The paper’s proposed SkinFlow focuses on dermatology, but it identifies the broader, field-level challenge of devising effective strategies to integrate and adapt general multimodal foundation models for medical use cases that demand clinically grounded understanding and decision support.