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

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

Abstract 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 diseas...

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Bibliographic Details
Main Authors: Andrew Maxwell, Runzhi Li, Bei Yang, Heng Weng, Aihua Ou, Huixiao Hong, Zhaoxian Zhou, Ping Gong, Chaoyang Zhang
Format: Article
Language:English
Published: BMC 2017-12-01
Series:BMC Bioinformatics
Subjects:
Deep neural networks
Deep learning
Intelligent health risk prediction
Multi-label classification
Medical health records
Online Access:http://link.springer.com/article/10.1186/s12859-017-1898-z

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http://link.springer.com/article/10.1186/s12859-017-1898-z

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