Applications of Federated Learning in Mobile Health: Scoping Review

The proliferation of mobile health (mHealth) applications is partly driven by the advancements in sensing and communication technologies, as well as the integration of artificial intelligence techniques. Data collected from mHealth applications, for example, on sensor devices carried by patients, ca...

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Bibliographic Details
Published in:	Journal of medical Internet research Vol. 25; no. 1; p. e43006
Main Authors:	Wang, Tongnian, Du, Yan, Gong, Yanmin, Choo, Kim-Kwang Raymond, Guo, Yuanxiong
Format:	Journal Article
Language:	English
Published:	Canada Gunther Eysenbach MD MPH, Associate Professor 01.05.2023 JMIR Publications
Subjects:	Administrative Personnel Application Artificial Intelligence Challenges Clinical decision making Collaborative learning Communication Communications technology Compression Databases, Factual Decision making Digital libraries Disease Disease Progression Epilepsy Health care industry Health services Health status Humans Limitations Machine learning Medical decision making Medical diagnosis Medical personnel Meta-analysis Mobile Applications Owners Parkinson's disease Patients Policy making Privacy Review Sampling Self care Sensors Smartphones Systematic review Telecommunications Telemedicine Wearable computers mHealth distributed systems privacy decision support health monitoring federated learning
ISSN:	1438-8871, 1439-4456, 1438-8871
Online Access:	Get full text
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