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An Interpretable Risk Prediction Model for Healthcare with Pattern Attention
2020-07-29
health informatics
Title + abstract only
View on medRxiv
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BackgroundThe 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: (i) There are lots of missing value for real value events, many methods impute the missing value and then train their models based on the imputed values, which may introduce imputation bias. The models performance is highly dependent on the imputation accurac...
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