A Framework of Rebalancing Imbalanced Healthcare Data for Rare Events' Classification: A Case of Look-Alike Sound-Alike Mix-Up Incident Detection

Identifying rare but significant healthcare events in massive unstructured datasets has become a common task in healthcare data analytics. However, imbalanced class distribution in many practical datasets greatly hampers the detection of rare events, as most classification methods implicitly assume...

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Detalles Bibliográficos
Autores principales: Zhao, Yang, Wong, Zoie Shui-Yee, Tsui, Kwok Leung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987310/
https://www.ncbi.nlm.nih.gov/pubmed/29951182
http://dx.doi.org/10.1155/2018/6275435

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987310/
https://www.ncbi.nlm.nih.gov/pubmed/29951182
http://dx.doi.org/10.1155/2018/6275435

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