An interpretable risk prediction model for healthcare with pattern attention

An interpretable risk prediction model for healthcare with pattern attention

Abstract Background The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer from three limitations: (1) There are lots of missing value for real valu...

Full description

Bibliographic Details
Main Authors: Sundreen Asad Kamal, Changchang Yin, Buyue Qian, Ping Zhang
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
EHR
Risk prediction
Self-attention
Interpretability
Online Access:https://doi.org/10.1186/s12911-020-01331-7

Internet

https://doi.org/10.1186/s12911-020-01331-7

Similar Items