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Can early risk prediction of CAD reduce the death rate?

Early risk prediction of CAD would be able to reduce the death rate by allowing early and targeted treatments. In healthcare, some studies applied data mining techniques and machine learning algorithms on the risk prediction of CAD using patient data collected by hospitals and medical centers.

What are the CAD predicting variables?

Based on the calculated weights, the following variables were selected as CAD predicting variables: gender, occupation, place of residence, family history, smoking status, comorbidity, mean value of pulse rate, TST waves status, hypertension history, chest pain, cholesterol, triglyceride, blood glucose level and creatinine level.

What is genotype-based CAD risk prediction?

The ultimate goal of genotype-based CAD risk prediction is to improve upon the discrimination and stratification offered by conventional risk factors alone. Genotype-based CAD risk prediction may eventually have clinical utility, but not without intrinsic complexities.

What does CAD stand for?

Anyone you share the following link with will be able to read this content: The main goal driving this work is to develop computer-aided classification models relying on clinical data to identify coronary artery disease (CAD) instances with high accuracy while incorporating the expert’s opinion as input, making it a "man-in-the-loop" approach.

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