Machine learning can accurately predict cardiovascular disease and guide treatment--but models that incorporate social determinants of health better capture risk and outcomes for diverse groups, finds ...
A research team used machine learning in an optimal experimental design to quickly find the best method for Li-ion battery charging in under 10 minutes, while also maximizing overall battery lifetime.
The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...
Machine learning for cardiovascular disease improves when social, environmental factors are included
Machine learning can accurately predict cardiovascular disease and guide treatment--but models that incorporate social determinants of health better capture risk and outcomes for diverse groups, finds ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback