Challenges in Federated Learning Trained Anomaly Detection Applied to Hospital Data without a Baseline-Reference-Cited by-同舟云学术

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Challenges in Federated Learning Trained Anomaly Detection Applied to Hospital Data without a Baseline

Published:2024-06-25 Issue: Volume:63 Page:1230-1235
ISSN:
Container-title:2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)
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Author:

Polido Susana¹,Napoli Otávio Oliveira²,Breternitz Mauricio³,de Almeida Ana Maria⁴

Affiliation:

1. Instituto Universitário de Lisboa (ISCTE-IUL),Lisbon,Portugal

2. UNICAMP,Institute of Computing,São Paulo,Brazil

3. Instituto Universitário de Lisboa (ISCTE-IUL),ISTAR,Lisbon,Portugal

4. Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR & CISUC, University of Coimbra,Lisbon,Portugal

Funder

Fundação para a Ciência e a Tecnologia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10608458/10608460/10608642.pdf?arnumber=10608642

Reference9 articles.

1. Why early detection of outbreaks is so important,2017

2. A SARS-CoV-2 Cluster in an Acute Care Hospital

3. An overview of anomaly detection techniques: Existing solutions and latest technological trends;Patcha,2007

4. Deep learning-based detection of covid-19 using wearables data;Bogu,2021

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