Enhancing the Trustworthiness of Deep Ensemble via Explainability in Medical Imaging
- 2 July 2026
- book chapter
- Published by Springer Nature
- p. 162-176
Abstract
No abstract availableKeywords
This publication has 19 references indexed in Scilit:
- Explainable ensemble deep learning-based model for brain tumor detection and classificationNeural Computing and Applications, 2024
- CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation2024
- Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysisArtificial Intelligence in Medicine, 2024
- A survey of uncertainty in deep neural networksArtificial Intelligence Review, 2023
- Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis2021
- Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks2020
- Dataset of breast ultrasound imagesData in Brief, 2020
- Ensembling Visual Explanations2018
- Deep Residual Learning for Image Recognition2016
- Learning Deep Features for Discriminative Localization2016