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Transparent and Clinically Interpretable AI for Lung Cancer Detection in Chest X-Rays
March 29, 2024, 4:42 a.m. | Amy Rafferty, Rishi Ramaesh, Ajitha Rajan
cs.LG updates on arXiv.org arxiv.org
Abstract: The rapidly advancing field of Explainable Artificial Intelligence (XAI) aims to tackle the issue of trust regarding the use of complex black-box deep learning models in real-world applications. Existing post-hoc XAI techniques have recently been shown to have poor performance on medical data, producing unreliable explanations which are infeasible for clinical use. To address this, we propose an ante-hoc approach based on concept bottleneck models which introduces for the first time clinical concepts into the …
abstract applications artificial artificial intelligence arxiv box cancer cancer detection cs.cv cs.lg data deep learning detection explainable artificial intelligence intelligence interpretable ai issue lung cancer medical medical data performance transparent trust type world xai
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