Predicting Chronic Myocardial Ischemia Using CCTA-Based Radiomics Machine Learning Nomogram
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DOI: 10.1007/s12350-020-02204-2
Abstract: Background Coronary computed tomography angiography (CCTA) is a well-established non-invasive diagnostic test for the assessment of coronary artery diseases (CAD). CCTA not only provides information on luminal stenosis but also permits non-invasive assessment and quantitative… read more here.
Keywords: radiomics machine; predicting chronic; machine learning; based radiomics ... See more keywords
Associations between Sex and Risk Factors for Predicting Chronic Kidney Disease
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DOI: 10.3390/ijerph19031219
Abstract: Gender is an important risk factor in predicting chronic kidney disease (CKD); however, it is under-researched. The purpose of this study was to examine whether gender differences affect the risk factors of early CKD prediction.… read more here.
Keywords: chronic kidney; risk factors; risk; prediction ... See more keywords