Chronic Disease Prediction Using Character-Recurrent Neural Network in The Presence of Missing Information
Abstract
The aim of this study was to predict chronic diseases in individual patients using a character-recurrent neural network (Char-RNN), which is a deep learning model that treats data in each class as a word when a large portion of its input values is missing. An advantage of Char-RNN is that it does not require any additional imputation method because it implicitly infers missing values considering the relationship with nearby data points. We...
Paper Details
Title
Chronic Disease Prediction Using Character-Recurrent Neural Network in The Presence of Missing Information
Published Date
May 27, 2019
Journal
Volume
9
Issue
10
Pages
2170 - 2170
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