Deep learning architectures for multi-label classification of intelligent health risk prediction

BACKGROUND: Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could have symptoms of multiple different diseases at th...

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Detalles Bibliográficos
Autores principales: Maxwell, Andrew, Li, Runzhi, Yang, Bei, Weng, Heng, Ou, Aihua, Hong, Huixiao, Zhou, Zhaoxian, Gong, Ping, Zhang, Chaoyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751777/
https://www.ncbi.nlm.nih.gov/pubmed/29297288
http://dx.doi.org/10.1186/s12859-017-1898-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751777/
https://www.ncbi.nlm.nih.gov/pubmed/29297288
http://dx.doi.org/10.1186/s12859-017-1898-z

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