GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification-Reference-Cited by-同舟云学术

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GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Published:2024-04 Issue: Volume:93 Page:103075
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Mahapatra Dwarikanath^ORCID,Bozorgtabar Behzad^ORCID,Ge Zongyuan^ORCID,Reyes Mauricio

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Innosuisse - Schweizerische Agentur für Innovationsförderung

Publisher

Elsevier BV

Reference73 articles.

1. A review of uncertainty quantification in deep learning: Techniques, applications and challenges;Abdar;Inf. Fusion,2021

2. Dataset of breast ultrasound images;Al-Dhabyani;Data Brief,2020

3. iNNvestigate neural networks;Alber;J. Mach. Learn. Res.,2019

4. Deep batch active learning by diverse, uncertain gradient lower bounds;Ash,2020

5. Layer normalization;Ba,2016

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Three-Stage Framework for Accurate Pediatric Chest X-ray Diagnosis Using Self-Supervision and Transfer Learning on Small Datasets;Diagnostics;2024-07-29

2. A comprehensive survey on deep active learning in medical image analysis;Medical Image Analysis;2024-07

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