This literature review indicates that AI tools can be used to support SPC clinicians in
decision-making and reduce manual workload, leading to potentially improved care and …

ABSTRACT BACKGROUND Artificial intelligence has emerged as a tool to potentially
increase efficiency and efficacy of healthcare and improve clinical outcomes. The growing …

Cardiac surgery patients are highly prone to severe complications post-discharge. Close
follow-up through remote patient monitoring can help detect adverse outcomes earlier or …

Abstract Remote Patient Monitoring (RPM) in cardiac surgery can become valuable for
clinicians to follow patients post-discharge closely. However, these services require …

Background Analysis of a single-channel electrocardiogram can potentially be used as a
screening method to detect systolic and diastolic dysfunction of the left ventricle. The …

Aim: We developed a machine learning model using EuroScore assumptions and
preoperative and intraoperative risk factors to predict mortality after coronary artery bypass …

Predicting post-discharge complications in cardiothoracic surgery is of utmost importance to
improve clinical outcomes. Machine Learning (ML) techniques have been successfully …

Postoperative complications after cardiac surgery can be severe and even fatal, making it a
high-risk procedure. Predicting surgical risk can guide the effective formulation of treatment …

High-risk cardiac surgery risk scoring provides patients and surgeons tangible information to
inform clinical decision making and allows for coherent patient and family discussion. These …

This paper aims to assess the efficiency, adaptiveness, and feasibility of various Machine
Learning Algorithms for predicting mortality rates inside the hospital. The predictors and …