Computer-aided detection (CADe) systems for colonoscopy promise to reduce clinical miss rates, yet reliable real-world deployment remains elusive. This translational gap stems in part from a structural flaw in model development: the reliance on curated datasets that under-represent the long negative stretches and proce...
Sebastian Doerrich, A. Schwab, Francesco Di Salvo et al.· 0 citations
Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts arise across institutions, acquisition protocols, and patient populations. VLMs enable zero-shot OOD detection by embedding images into a language-aligned latent space, where cross-modal similarity serves as a...
Shyam Nandan Rai, Francesco Di Salvo, Sebastian Doerrich et al.· 0 citations
MoPET, a mixture-of-experts (MoE) method that uses a learned sparse router to direct each input through a small subset of low-rank PEFT experts injected into a frozen foundation model, sharing capacity across datasets while limiting cross-domain gradient conflict is proposed.
Sebastian Doerrich, Daniel Würtinger, Francesco Di Salvo et al.· arXiv.org· 0 citations
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