TA-RNN: an Attention-based Time-aware Recurrent Neural Network Architecture for Electronic Health Records

Motivation: Electronic Health Records (EHR) represent a comprehensive resource of a patient's medical history. EHR are essential for utilizing advanced technologies such as deep learning (DL), enabling healthcare providers to analyze extensive data, extract valuable insights, and make precise and data-driven clinical decisions. DL methods such as Recurrent Neural Networks (RNN) have been utilized to analyze EHR to model disease progression and predict diagnosis. However, these methods do not address some inherent irregularities in EHR data such as irregular time …

advanced analyze architecture attention clinical cs.ai cs.lg data data-driven decisions deep learning ehr electronic electronic health records enabling extract health healthcare healthcare providers history insights medical motivation network network architecture neural network patient records recurrent neural network rnn technologies