Qian, K;
Zhang, L;
Li, K;
Liu, J;
(2021)
Editorial: Machine Learning for Non/Less-Invasive Methods in Health Informatics.
Frontiers in Digital Health
, 3
, Article 763109. 10.3389/fdgth.2021.763109.
(In press).
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| Type: | Article |
|---|---|
| Title: | Editorial: Machine Learning for Non/Less-Invasive Methods in Health Informatics |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fdgth.2021.763109 |
| Publisher version: | https://doi.org/10.3389/fdgth.2021.763109 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Artificial intelligence, deep learning, digital health, intelligent medicine, machine learning, medicine 4.0, non/less-invasive methods |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10141980 |
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