Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

Subjects: “…assess microvascular function…”

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning by Bernhard Vennemann (7434353)

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System pharmacology-based determination of the functional components and mechanisms in chronic heart failure treatment: an example of Zhenwu decoction by Yisheng Huang (152457)

“…To discern vital components, a novel dynamic programming algorithm was devised and used to determine the core component group (CCG) within the CFAS. …”

The expert screening cost <i>g</i>_expert(<i>x</i>) defined for the Challenge: Mean cost for screening a fraction <i>x</i> of a patient cohort for cardiac abnormalities. by Matthew A. Reyna (16965038)

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The expert screening cost <i>g</i>_expert(<i>x</i>) defined for the Challenge: Mean cost for screening a fraction <i>x</i> of a patient cohort for cardiac abnormalities. by Matthew A. Reyna (16965038)

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Test section including model of the aortic root with BHV and a flow sensor at the ascending aorta. by Bernhard Vennemann (7434353)

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Demographic, murmur, and clinical outcome information in the Challenge training, validation, and/or test sets; nan values indicate unknown or missing values. by Matthew A. Reyna (16965038)

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Demographic, murmur, and clinical outcome distributions across the Challenge training, validation, and test data. by Matthew A. Reyna (16965038)

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Weighted accuracy metric (1) for the murmur detection task (<i>x</i>-axis) and the cost metric (8) scores for the clinical outcome identification task (<i>y</i>-axis) of the final... by Matthew A. Reyna (16965038)

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Scores of the officially ranked methods on the test set for the clinical outcome identification task. by Matthew A. Reyna (16965038)

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Auscultation locations for the CirCor DigiScope dataset [6], which was used for the Challenge: Pulmonary valve (PV), aortic valve (AV), mitral valve (MV), and tricuspid valve (TV). by Matthew A. Reyna (16965038)

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Traditional evaluation metric (<i>x</i>-axis) and cost metric (<i>y</i>-axis) scores for the final Challenge entries with the clinical outcome identification task on the hidden tes... by Matthew A. Reyna (16965038)

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Traditional evaluation metric (<i>x</i>-axis) and weighted accuracy metric (<i>y</i>-axis) scores for the final Challenge entries with the murmur detection task on the hidden test... by Matthew A. Reyna (16965038)

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Confusion matrix <i>N</i> for clinical outcome detection with two classes: Clinical outcome abnormal and clinical outcome normal. by Matthew A. Reyna (16965038)

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Screening and diagnosis pipeline for the Challenge. by Matthew A. Reyna (16965038)

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Confusion matrix <i>M</i> for murmur detection with three classes: Murmur present, murmur unknown, and murmur absent. by Matthew A. Reyna (16965038)

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Scores of the officially ranked methods on the test set for the murmur detection task. by Matthew A. Reyna (16965038)

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Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

Rim data percentage for multimorbid individuals as a function of the number of clusters. by Anders Stockmarr (405316)