BACKGROUND: @entity301 / @entity453 (CHDs/CAD), the most common form of @entity65 ( @entity65 ), are a major cause for @entity204 and disability in developing/developed countries. CAD risk factors could be detected by physicians to prevent the CAD occurrence in the near future. Invasive coronary angiography, a current diagnosis method, is costly and associated with morbidity and mortality in CAD @entity1 . The aim of this study was to design a computer-based noninvasive CAD diagnosis system with clinically interpretable rules. MATERIALS AND METHODS: In this study, the Cleveland CAD dataset from the University of California UCI (Irvine) was used. The interval-scale variables were discretized, with cut points taken from the literature. A fuzzy rule-based system was then formulated based on a neuro-fuzzy classifier (NFC) whose learning procedure was speeded up by the scaled conjugate gradient algorithm. Two feature selection (FS) methods, multiple logistic regression (MLR) and sequential FS, were used to reduce the required attributes. The performance of the NFC (without/with FS) was then assessed in a hold-out validation framework. Further cross-validation was performed on the best classifier. RESULTS: In this dataset, 16 complete attributes along with the binary CHD diagnosis (gold standard) for 272 subjects (68% male) were analyzed. MLR + NFC showed the best performance. Its overall sensitivity, specificity, accuracy, @entity2246 (a) and statistical power were 79%, 89%, 84%, 0.1 and 79%, respectively. The selected features were "age and ST/heart rate slope categories," "exercise-induced @entity951 status," fluoroscopy, and @entity4214 -201 stress scintigraphy results. CONCLUSION: The proposed method showed "substantial agreement" with the gold standard. This algorithm is thus, a promising tool for screening CAD @entity1 .

A noninvasive method for XXXX diagnosis using a clinically-interpretable fuzzy rule-based system.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity301 :: ('MESH:D003327', 'Disease') :: ['Coronary heart diseases'] @entity4214 :: ('MESH:D013793', 'Chemical') :: ['thallium'] @entity951 :: ('MESH:D000787', 'Disease') :: ['angina'] @entity453 :: ('MESH:D003324', 'Disease') :: ['coronary artery diseases'] @entity204 :: ('MESH:D003643', 'Disease') :: ['death'] @entity65 :: ('MESH:D002318', 'Disease') :: ['CVD', 'cardiovascular disease'] @entity2246 :: ('MESH:D008661', 'Disease') :: ['type I error']
@entity453 :: (MESH:D003324,Disease) :: ['coronary artery diseases']
