Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images-Reference-Cited by-同舟云学术

Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images

Published:2022-11 Issue:11 Volume:26 Page:5344-5354
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Chen Siying¹^ORCID,Liu Minghui²^ORCID,Deng Pan²,Deng Jiali²^ORCID,Yuan Yi³,Cheng Xuan²,Xie Tianshu²^ORCID,Xie Libo⁴,Zhang Wei⁵,Gong Haigang²^ORCID,Wang Xiaomin⁶,Xu Lifeng⁶,Pu Hong³,Liu Ming²^ORCID

Affiliation:

1. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, ZheJiang, China

2. University of Electronic Science and Technology, Chengdu, Sichuan, China

3. Department of Radiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospitals, Chengdu, Sichuan, China

4. Department of Urology, Sichuan Clinical Research Center for Nephropathy, Luzhou, Sichuan, China

5. Department of Nuclear Medicine, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospitals, Chengdu, Sichuan, China

6. Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, Zhejiang, China

Funder

Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China

Municipal Government of Quzhou

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/9945616/09855449.pdf?arnumber=9855449

Reference41 articles.

1. Explainable AI for COVID-19 CT Classifiers: An Initial Comparison Study

2. Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond

3. Synthesis of gadolinium-enhanced liver tumors on nonenhanced liver MR images using pixel-level graph reinforcement learning

4. Sequential conditional reinforcement learning for simultaneous vertebral body detection and segmentation with modeling the spine anatomy

5. Partial Policy-Based Reinforcement Learning for Anatomical Landmark Localization in 3D Medical Images

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