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Self-eXplainable AI for Medical Image Analysis: A Survey and New
  Outlooks
v1v2 (latest)

Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

3 October 2024
Junlin Hou
Sicen Liu
Yequan Bie
Hongmei Wang
Andong Tan
Luyang Luo
Hao Chen
    XAI
ArXiv (abs)PDFHTML

Papers citing "Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks"

4 / 4 papers shown
Title
MVP-CBM:Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification
MVP-CBM:Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification
Chunjiang Wang
Kun Zhang
Y. Liu
Zhiyang He
Xiaodong Tao
S. Kevin Zhou
15
0
0
14 Jun 2025
Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
Alice Natalina Caragliano
Claudia Tacconi
Carlo Greco
Lorenzo Nibid
E. Ippolito
Michele Fiore
G. Perrone
Sara Ramella
Paolo Soda
V. Guarrasi
83
0
0
02 May 2025
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.2K
22,272
0
22 May 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.3K
17,178
0
16 Feb 2016
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