Deep learning applied to automatic disease detection using chest X‐rays
Author:
Affiliation:
1. Graduate School of Biomedical Engineering Faculty of Engineering University of New South Wales Sydney New South Wales Australia
2. Department of Medical Imaging Prince of Wales Hospital Sydney New South Wales Australia
Publisher
Wiley
Subject
Radiology, Nuclear Medicine and imaging,Oncology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/1754-9485.13273
Reference147 articles.
1. YosinskiJ CluneJ BengioY LipsonH.How transferable are features in deep neural networks?2014 November 01 2014:[arXiv:1411.792 p.]. Available from:https://ui.adsabs.harvard.edu/abs/2014arXiv1411.1792Y
2. WangX PengY LuL LuZ BagheriM SummersRM(eds).ChestX‐Ray8: Hospital‐Scale Chest X‐Ray Database and Benchmarks on Weakly‐Supervised Classification and Localization of Common Thorax Diseases. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2017 21‐26 July 2017.
3. SirazitdinovI KholiavchenkoM KuleevR IbragimovB.Data Augmentation for Chest Pathologies Classification 2019;1216–9.
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