Editorial: Artificial intelligence for smart health: learning, simulation, and optimization

Bing Yao; Nathan Gaw; Hyo Kyung Lee

doi:10.3389/fphys.2024.1541057

Editorial: Artificial intelligence for smart health: learning, simulation, and optimization

Front Physiol. 2024 Dec 23:15:1541057. doi: 10.3389/fphys.2024.1541057. eCollection 2024.

Authors

Bing Yao¹, Nathan Gaw², Hyo Kyung Lee³

Affiliations

¹ Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, TN, United States.
² Department of Operational Sciences, Air Force Institute of Technology, Wright-Patterson AFB, OH, United States.
³ School of Industrial Management and Engineering, Korea University, Seoul, Republic of Korea.

No abstract available

Keywords: data mining; health informatics; machine learning and AI; simulation optimization; smart health.

Publication types

Editorial

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Author BY acknowledges the funding support from the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number R01HL172292. Author HL is funded by the National Research Foundation (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00212713). Author NG is funded by Air Force Office of Scientific Research (AFOSR) Grant No. 23AFCOR003 under the Dynamic Data and Information Processing (DDIP) program.