Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

ABSTRACT:

Objective

To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoing research and identify open challenges in building deep learning models of EHRs.

Design/method

We searched PubMed and Google Scholar for papers on deep learning studies using EHR data published between January 1, 2010, and January 31, 2018. We summarize them according to these axes: types of analytics tasks, types of deep learning model architectures, special challenges arising from health data and tasks and their potential solutions, as well as evaluation strategies.

Results

We surveyed and analyzed multiple aspects of th

SUBMITTER: Xiao C 

PROVIDER: S-EPMC6188527 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature