Intraoperative Hypotension Prediction Based on Features Automatically Generated Within an Interpretable Deep Learning Model-Reference-Cited by-同舟云学术

Intraoperative Hypotension Prediction Based on Features Automatically Generated Within an Interpretable Deep Learning Model

Published:2023 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Hwang Eugene¹^ORCID,Park Yong-Seok²^ORCID,Kim Jin-Young³,Park Sung-Hyuk¹^ORCID,Kim Junetae⁴^ORCID,Kim Sung-Hoon²^ORCID

Affiliation:

1. School of Management Engineering, Korea Advanced Institute of Science and Technology, Seoul, Republic of Korea

2. Department of Anesthesiology and Pain Medicine, Asan Medical Center, Biosignal Analysis and Perioperative Outcome Research Laboratory, University of Ulsan College of Medicine, Seoul, Republic of Korea

3. Asan Medical Center, and the Department of Medical Engineering, Biosignal Analysis and Perioperative Outcome Research Laboratory, Department of Anesthesiology and Pain Medicine, University of Ulsan College of Medicine, Seoul, Republic of Korea

4. Graduate School of Cancer Science and Policy and the Healthcare AI Team, National Cancer Center, Goyang, Republic of Korea

Funder

National Cancer Center

Ministry of Health and Welfare, Republic of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10130807.pdf?arnumber=10130807

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