Machine-Learning Diagnosis
Traditional obstructive-CAD risk tools can label ANOCA patients low-risk and reduce access to further testing or intensive therapy. Traditional stress testing may miss occult coronary abnormalities in ANOCA. The first modelling objective i…
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Traditional obstructive-CAD risk tools can label ANOCA patients low-risk and reduce access to further testing or intensive therapy. Traditional stress testing may miss occult coronary abnormalities in ANOCA. The first modelling objective is to estimate the pretest probability that an angina patient has ANOCA rather than obstructive CAD. The diagnostic probability is intended to guide decisions about angiography, non-invasive testing, and coronary function testing.