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Indirectly-Supervised Anomaly Detection of Clinically-Meaningful Health Events from Smart Home Data

Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not of interest, obscuring relevant anomalies. In this work, we improve upon traditional anomaly detection methods by introducing Isudra, an Ind...

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Detalles Bibliográficos
Publicado en:ACM Trans Intell Syst Technol
Autores principales: DAHMEN, JESSAMYN, COOK, DIANE J.
Formato: Artigo
Lenguaje:Inglês
Publicado: 2021
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Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC8323613/
https://ncbi.nlm.nih.gov/pubmed/34336375
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1145/3439870
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