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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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Détails bibliographiques
Publié dans:ACM Trans Intell Syst Technol
Auteurs principaux: DAHMEN, JESSAMYN, COOK, DIANE J.
Format: Artigo
Langue:Inglês
Publié: 2021
Sujets:
Accès en ligne: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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