A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

Adverse neighborhood conditions in early adulthood may raise the risk of early cardiovascular disease decades later.

OCHIN researchers describe project designed to improve risk estimates by combining clinical information with patients’ lived ...

Most Americans eat too much fat and too many calories. Along with a lack of exercise, this has led to an epidemic of obesity and diabetes. It's also contributed to keeping heart disease as the leading ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

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Abstract: Heart disease remains a leading cause of mortality worldwide, necessitating early and accurate detection to improve patient outcomes. This paper presents a Heart Disease Prediction System ...

ProPublica is a nonprofit newsroom that investigates abuses of power. This story first ran in Dispatches, our weekly newsletter from our reporters about their recent investigations. Sign up to receive ...

Abstract: This paper suggests a machine learning and deep learning hybrid model to predict cardiac diseases in a better way with the use of a Cleveland dataset. The methodology integrates classical ML ...