A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism

BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suitability for applications where there is a lack of...

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Detalles Bibliográficos
Autores principales: Woldaregay, Ashenafi Zebene, Launonen, Ilkka Kalervo, Albers, David, Igual, Jorge, Årsand, Eirik, Hartvigsen, Gunnar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450372/
https://www.ncbi.nlm.nih.gov/pubmed/32784179
http://dx.doi.org/10.2196/18912

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450372/
https://www.ncbi.nlm.nih.gov/pubmed/32784179
http://dx.doi.org/10.2196/18912

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