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Interpretable Machine Learning for COVID-19: An Empirical Study on
  Severity Prediction Task

Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task

30 September 2020
Han-Ching Wu
Wenjie Ruan
Jiangtao Wang
Dingchang Zheng
Bei Liu
Yayuan Gen
Xiangfei Chai
Jian Chen
Kunwei Li
Shaolin Li
A. Helal
ArXivPDFHTML

Papers citing "Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task"

4 / 4 papers shown
Title
Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations
Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations
Dima Alattal
Asal Khoshravan Azar
P. Myles
Richard Branson
Hatim Abdulhussein
Allan Tucker
29
0
0
10 May 2025
Explainable Artificial Intelligence Methods in Combating Pandemics: A
  Systematic Review
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review
F. Giuste
Wenqi Shi
Yuanda Zhu
Tarun Naren
Monica Isgut
Ying Sha
L. Tong
Mitali S. Gupte
May D. Wang
18
73
0
23 Dec 2021
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,235
0
24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
251
3,683
0
28 Feb 2017
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