Blood Biomarkers Predict Cardiac Workload Using Machine Learning.

Introduction: Rate pressure product (the product of heart rate and systolic blood pressure) is a measure of cardiac workload. Resting rate pressure product (rRPP) varies from one individual to the next, but its biochemical/cellular phenotype remains unknown. This study determined the degree to which an individual's biochemical/cellular profile as characterized by a standard blood panel is predictive of rRPP, as well the importance of each blood biomarker in this prediction.

Waist circumference prediction for epidemiological research using gradient boosted trees.

Background: Waist circumference is becoming recognized as a useful predictor of health risks in clinical research. However, clinical datasets tend to lack this measurement and self-reported values tend to be inaccurate. Predicting waist circumference from standard physical features could be a viable method for generating this information when it is missing or mitigating the impact of inaccurate self-reports.