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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...
Kaydedildi:
| Yayımlandı: | J Med Internet Res |
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| Asıl Yazarlar: | , , , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
JMIR Publications
2020
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7450372/ https://ncbi.nlm.nih.gov/pubmed/32784179 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2196/18912 |
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