Key result
Machine learning and data mining methods provide promising non-invasive computational approaches for the early diagnosis of coronary artery disease.
Why the study?
Do machine learning and computational methods improve the early, non-invasive diagnosis of coronary artery disease?
Do machine learning and computational methods improve the early, non-invasive diagnosis of coronary artery disease?
Machine learning and data mining techniques offer promising, non-invasive, and cost-effective alternatives to coronary angiography for the early diagnosis of coronary artery disease.
Supports ML exploration for non-invasive CAD diagnosis; leaves open prospective validation before clinical adoption.
scholarly articles on cardiology Journal of Cardiology & Cardiovascular Therapy is an Open Access, international peer reviewed journal launched from Juniper Publishers. Cardiology is a branch of medicine deals with the disorders of heart that keeps cardiologists up to date with advances in the diagnosis and treatment of cardiovascular diseases.
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Luxmi Verma (2018) conducted a review in Coronary Artery Disease. Machine learning methods was evaluated. Machine learning and data mining methods provide promising non-invasive computational approaches for the early diagnosis of coronary artery disease.
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