Enhancing Patient Outcome Prediction through Deep Learning with Sequential Diagnosis Codes from structural EHR: A systematic review (Preprint)
Tuankasfee Hama,
Mohanad Alsaleh,
Freya Allery
et al.
Abstract:BACKGROUND
There has been a rapid growth in the application of structured Electronic Health Records (EHRs) to healthcare systems, where huge amounts of diagnosis codes presenting the temporal event of the patient are collected. In the era of artificial intelligence, many models, especially Deep Learning (DL), are applied for patient outcome prediction. This systematic review aimed to identify DL models developed for sequential diagnosis codes for patient outcome prediction.
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