Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …

Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …

Predicting a patient's future health condition by analyzing their Electronic Health Records
(EHRs) is a trending subject in the intelligent medical field, which can help clinicians …

Abstract Electronic Health Records (EHRs) significantly enhance clinical decision-making,
particularly in safe and effective medication recommendation based on complex patient …

Disease prediction based on patients' historical admission records is an essential task in the
medical field, but current predictive models often lack interpretability, which is a critical …

Patient similarity search is an essential task in healthcare. Recent studies adopted electronic
health records (EHRs) to learn patient representations for measuring the clinical similarities …

Predicting hospital readmission with effective machine learning techniques has attracted a
great attention in recent years. The fundamental challenge of this task stems from …

Background/Objectives: Predicting patient readmission is an important task for healthcare
risk management, as it can help prevent adverse events, reduce costs, and improve patient …

Background Emergency room reports pose specific challenges to natural language
processing techniques. In this setting, violence episodes on women, elderly and children are …

Abstract Purpose of Review Application of deep learning (DL) is growing in the last years,
especially in the healthcare domain. This review presents the current state of DL techniques …