We developed statistical and machine learning models to predict premature death from the presence of 17 chronic conditions and the patients’ age at diagnosis. We evaluated models using accuracy, ...

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

Scientists discuss a machine learning-based tool that can detect Parkinson's disease years before the first onset of symptoms.

Scientists have found a way to predict Alzheimer's Disease up to seven years before symptoms appear by analyzing patient records with machine learning.

UCSF scientists found a way to predict Alzheimer’s disease up to seven years before symptoms appear by analyzing patient records with machine learning. Conditions that most influenced prediction of ...

For example, by preventing hospitalizations in cases of just two widespread chronic illnesses — heart disease and diabetes — the United States could save billions of dollars a year.