Application of Deep Learning to EHR systems

Earlier this year American researchers Xiao, Choi and Sun published a systematic review about the application of deep learning methods to extract and analyse EHR data in the prestigious JAMIA journal. The 4 categories of analytic tasks that they found deep learning was being used were 1) Disease Detection/Classification 2) Sequential prediction of clinical events 3) Concept embedding where feature representations are derived algorithmically from EHR 4) Data augmentation whereby realistic data elements or patient records are created and 5) EHR data privacy where deep learning was used to protect patient privacy. More importantly, they identified challenges in the application and corresponding solutions. I have summarised the issues and solutions in this table: