A study led by scientists at King's has revealed how the physical orientation of the heart inside the chest dramatically ...

Abstract Purpose Recent advances in machine learning have led to the development of classifiers that predict molecular subtypes of acute lymphoblastic leukemia (ALL) using RNA-sequencing (RNA-seq) ...

As data volumes surge across every industry and machine learning tools become more accessible, predictive analytics is evolving from a niche discipline into a cornerstone of application innovation.

Abstract The accurate and early detection of coronary heart disease (CHD) is crucial for reducing mortality rates. This study evaluates the predictive performance of three machine learning ...

Deep machine-learning speeds assessment of fruit fly heart aging and disease, a model for human disease Use of high-speed video microscopy and artificial intelligence provides calculated ...

A machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous recognized categorization methods.

To solve this issue, predicting early heart disease is important. This research focuses on supervised machine learning techniques as a potential tool for heart disease prediction. This study has done ...

To get an inside look at the heart, cardiologists often use electrocardiograms (ECGs) to trace its electrical activity and magnetic resonance images (MRIs) to map its structure. Because the two ...