The goal of this observational and diagnostic study is to develop and validate an artificial intelligence assisted approach for coronary computer tomography angiography-(CCTA)-based screening and diagnosis of cardiomyopathies in patients with suspected coronary artery diseases. This study aims to develop a computerized CCTA interpretation using artificial intelligence for multi-label classification task to assist cardiomyopathy diagnosis in the clinical workflow.
A clinical diagnosis of cardiomyopathies, including hypertrophic cardiomyopathy, dilated cardiomyopathy, restrictive cardiomyopathy, cardiac amyloidosis, myocarditis, arrhythmogenic right ventricular cardiomyopathy, and coronary artery disease/ischemic heart disease.
At least one CCTA before surgery or implantable device treatment.
No recorded diagnosis of cardiomyopathy or undetermined type of cardiomyopathy.
A clinical diagnosis of secondary cardiac abnormalities due to other organic or systemic diseases.
Surgery or implantable device treatment before CCTA examination.
Inclusion Criteria: participants with at least one CCTA examination.