Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking.

Saved in:

Bibliographic Details
Title:	Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking.
Authors:	Pavlidis, Nikolaos^1,2, asendros@athenarc.grnikolaos.pavlidis@athenarc.gr, Sendros, Andreas^1,2, ttsiolak@ee.duth.gr, Tsiolakis, Theodoros^1,2, periklis.kostamis@athenarc.gr, Kostamis, Periklis^1,2, c.karasoulas@athenarc.gr, Karasoulas, Christos^1,2, eleni.briola@athenarc.gr, Briola, Eleni^1,2, christos.nikolaidis@athenarc.gr, Nikolaidis, Christos Chrysanthos^1,2, vperifan@athenarc.gr, Perifanis, Vasilis^1,2, gdrosato@athenarc.gr, Drosatos, George¹, eli@athenarc.gr, Katsiri, Eleftheria^1,2, pefraimi@athenarc.gr, Filippidou, Despoina Elisavet³, eli@opsis-research.ro, Manos, Anastasios³, tasos.manos@gmail.com, Efraimidis, Pavlos S.^1,2
Source:	Journal of Sensor & Actuator Networks; Feb2025, Vol. 14 Issue 1, p11, 23p
Database:	Applied Science & Technology Source

Description
ISSN:	22242708
DOI:	10.3390/jsan14010011