NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical
Development Patterns of Preterm Infants

NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants

1 January 2023

Fan Wang

Deyu Meng

Papers citing "NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants"

6 / 6 papers shown

Title
SurfGNN: A robust surface-based prediction model with interpretability for coactivation maps of spatial and cortical features Zhuoshuo Li Jiong Zhang Youbing Zeng Jiaying Lin Dan Zhang Jianjia Zhang Duan Xu H. Kim Bingguang Liu Mengting Liu 19 0 0 05 Nov 2024
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis Hejie Cui Wei Dai Yanqiao Zhu Xiaoxiao Li Lifang He Carl Yang 66 77 0 30 Jun 2022
Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models Zixuan Liu Ehsan Adeli K. Pohl Qingyu Zhao FAtt MedIm 16 8 0 16 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 162 589 0 31 Dec 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 278 10,544 0 19 Feb 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,801 0 25 Nov 2016