Explainable Methods for Computer-Aided Diagnosis: Anuja Vats (NTNU)
Автор: SFI Visual Intelligence
Загружено: 2025-05-26
Просмотров: 115
Anuja Vats, a Postdoctoral Researcher at DART and Colorlab, Department of Computer Science, NTNU, gave a presentation titled "Explainable Methods for Computer-Aided Diagnosis" on May 22nd as part of the Visual Intelligence Online Seminar series.
Abstract:
For AI assistance to gain meaningful clinical acceptance, it must be paired with explainability - a slippery concept that needs to be tailored to domain and application needs.
In this talk, I will present explainable methods for computer-aided diagnostic tasks, with a focus on wireless capsule endoscopy - a challenging domain due to the complexity and variability of gastrointestinal imagery. I will explore three complementary approaches to explanation: counterfactual explanations that illustrate "what-if" scenarios, uncertainty quantification methods that communicate model confidence, and briefly touch upon concept-based interpretability techniques that can align with medical reasoning patterns.
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