Processing of Electronic Health Records using Deep Learning: A review

TL;DR

This review discusses how deep learning techniques are transforming healthcare by enabling the secondary use of large-scale electronic health records and data from health devices, fostering new research and clinical applications.

Contribution

It provides a comprehensive overview of recent deep learning methods applied to electronic health records and wearable device data in healthcare.

Findings

Deep learning enhances analysis of electronic health records.

Integration of wearable device data improves health monitoring.

Deep learning accelerates healthcare research and decision-making.

Abstract

Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of healthcare data is beginning to revolutionize healthcare. Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) and data generated from health and wellbeing devices (such as personal trackers), a significant contribution to this trend is also being made by recent advances on machine learning, specifically deep learning algorithms.