Evaluation of Sequential and Temporally Embedded Deep Learning Models for Health Outcome Prediction

Deep learning sequential models are increasingly being used to predict patients’ health outcomes by analyzing their medical histories. In this paper, we investigate the design decisions and challenges of using deep learning sequential models for predictive health modeling. Our results show that the most successful deep learning health models to date, called transformers, lack a mechanism to analyze the temporal characteristics of health …