Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

METHODS: Using unselected 14-day single-lead ambulatory ECG recordings, we developed a deep learning model to identify patients with prior asystole from sinus arrest or complete heart block.

Among these classifiers, RF exhibits a remarkable accuracy of 98%. The results demonstrate the superior performance of the proposed approach for heartbeat classification systems. ECG signal ...

Different machine learning (ML)-based methods are utilized to detect BBB from the fifth-order tensor-domain features of each subject’s entire duration 12-lead ECG recording. The suggested approach is ...

Understanding diffusion in charged and crowded media is crucial for solving a wide range of biological and materials challenges. Classifying diffusion by traditional methods such as mean square ...

Advanced Supervised Machine Learning Techniques for Accurate Prediction of Diabetes Mellitus Using Feature Selection Provisionally accepted ...