ICAM: Interpretable Classification via Disentangled Representations and
Feature Attribution Mapping

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping

15 June 2020

Mariana da Silva

Carole Sudre

Petru-Daniel Tudosiu

Stephen M. Smith

Papers citing "ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping"

5 / 5 papers shown

Title
Disentangling representations of retinal images with generative models Sarah Muller Lisa M. Koch Hendrik P. A. Lensch Philipp Berens MedIm 32 3 0 29 Feb 2024
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images Yusuf Brima M. Atemkeng FAtt MedIm 29 0 0 01 Aug 2022
Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligence H. Nguyen Michael Clement Boris Mansencal Pierrick Coupé MedIm 33 6 0 07 Jun 2022
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 18 302 0 01 Nov 2021
Challenges for machine learning in clinical translation of big data imaging studies Nicola K. Dinsdale Emma Bluemke V. Sundaresan M. Jenkinson Stephen Smith Ana I. L. Namburete AI4CE 32 41 0 07 Jul 2021