MedConcept: Unsupervised Concept Discovery for Interpretability in Medical VLMs

MedConcept is an unsupervised framework that uncovers latent medical concepts from pretrained Vision-Language Models (VLMs), translating neuron-level activations into clinically verifiable text summaries. This advancement enhances the interpretability of medical VLMs by providing concept-level explanations, crucial for building trust in clinical applications and enabling more transparent model reasoning.

Read the full article at arXiv cs.CV (Vision)

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