Aim Artificial intelligence (AI) and machine learning (ML) are important areas of computer
science that have recently attracted attention for their application to medicine. However, as …

Introduction Growth of machine learning (ML) in healthcare has increased potential for
observational data to guide clinical practice systematically. This can create self-fulfilling …

Abstract Purpose of Review This literature review aims to provide a comprehensive
overview of the recent advances in prediction models and the deployment of AI and ML in …

Background: Cardiac arrest is a life-threatening cessation of activity in the heart. Early
prediction of cardiac arrest is important, as it allows for the necessary measures to be taken …

Background One of the significant problems in the field of healthcare is the low survival rate
of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest …

Background Resuscitated cardiac arrest is associated with high mortality; however, the
ability to estimate risk of adverse outcomes using existing illness severity scores is limited …

Clinicians' decision-making is of utmost importance during critical situations. Thus,
integrating Clinical Decision Support Systems (CDSS) may assist the medical staff by …

Aim The emergence and evolution of artificial intelligence (AI) has generated increasing
interest in machine learning applications for health care. Specifically, researchers are …

The field of artificial intelligence (AI) has been developing more prominently for over half a
century. Innovations in computer processing power and analytical capabilities coupled with …

Background Although machine learning-based prediction models for in-hospital cardiac
arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital …