The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
IEEE

A Self-Supervised Framework for Multi-Function Radar Signal Sequence Prediction

Abstract: Predicting multi-function radar (MFR) signal sequences is essential for radar signal analysis. Traditional methods often face challenges due to noise and outliers in intercepted signal ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Opinion
Dot Physics on MSNOpinion

Comparing linear and rotational motion: kinematics and equations

Dive into the world of motion by exploring the similarities and differences between linear and rotational kinematics. In this video, we break down key concepts, equations, and relationships that ...
IEEE

Surface-PMSM Sensorless Control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating With Prediction Error Rolling Compensation

Abstract: Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors due to its strong robustness against measurement and system noise. However, ...