Editorial: Machine Learning for Non/Less-Invasive Methods in Health Informatics

Kun Qian; Liang Zhang; Kezhi Li; Juan Liu

doi:10.3389/fdgth.2021.763109

Editorial: Machine Learning for Non/Less-Invasive Methods in Health Informatics

Front Digit Health. 2021 Oct 6:3:763109. doi: 10.3389/fdgth.2021.763109. eCollection 2021.

Authors

Kun Qian¹, Liang Zhang^{2

3}, Kezhi Li⁴, Juan Liu⁵

Affiliations

¹ School of Medical Technology, Beijing Institute of Technology, Beijing, China.
² School of Computer Science and Technology, Xidian University, Xi'an, China.
³ Xi'an Key Laboratory of Intelligent Software Engineering, Xidian University, Xi'an, China.
⁴ Institute of Health Informatics (IHI), University College London (UCL), London, United Kingdom.
⁵ Department of Plastic Surgery, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

No abstract available

Keywords: artificial intelligence; deep learning; digital health; intelligent medicine; machine learning; medicine 4.0; non/less-invasive methods.

Publication types

Editorial