Scripps Research study combines AI, genomics, and health records to create personalized heart attack risk predictions. ABC ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and ...

Software developed using machine learning can be used to predict someone’s risk of heart disease in less than a minute by analyzing the veins and arteries in their eye. The new research ...

In it, the researchers described how they’d first trained the algorithms to predict heart disease risk from 608 medical variables, then narrowed that down to just 47 key indicators. The ...

This is the largest study of its kind to date and the results show for the first time the relative importance of the three major families of lipoprotein for the potential risk of heart disease." ...

such as heart disease and stroke, more accurately than before. The tool, called QR4, can help ­identify these ­diseases in particular high-risk ­patients, which current ­prediction tools can miss.

“The second was that, in place of race, using social determinants of health did not increase accuracy and prediction of ... CVD risk factors for heart disease; and include components such ...

Development and Evaluation of a Comprehensive Prediction Model for Incident Coronary Heart Disease Using Genetic, Social, and Lifestyle-Psychological Factors ...

Also for the first time, the new calculator takes kidney function into account when predicting risk, as kidney disease puts people at higher risk of heart disease, heart attacks, heart failure and ...