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

Subjects:

Critical values of membership functions learned from the study cohort by the algorithm. by Yufeng Zhang (195768)

EALM algorithm. by Weibo Wang (782424)

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

Subjects: “…assess microvascular function…”

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

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)

Subjects:

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

“…Subsequently, a pioneering method for evaluating node significance was formulated, culminating in the creation of core functional association space (CFAS). To discern vital components, a novel dynamic programming algorithm was devised and used to determine the core component group (CCG) within the CFAS. …”

Comparative analysis of algorithms. by Xumin Zhao (18261643)

Subjects:

Data extraction and patient algorithm. by Jennifer M. Kwan (3350321)

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

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

Subjects:

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

Subjects:

The phases of automated BHV monitoring. by Bernhard Vennemann (7434353)

Subjects:

Baseline one-class SVM model. by Bernhard Vennemann (7434353)

Subjects:

Comparison of different optimization algorithms. by Hang Zhao (143592)

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

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…The Pareto optimal front was generated using MOCOA with the indicators of spectral kurtosis and KL divergence, by which the optimal intrinsic mode functions were obtained. …”

Flowchart of the clinical decision support system and the interpretable tropical geometry-based fuzzy neural network algorithm. by Yufeng Zhang (195768)

Image_1_Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.TIFF by Hao Chen (5190)

“…</p>Conclusion<p>This study identified ten energy metabolism-related diagnostic markers using random forest algorithm, which may help optimize risk stratification and clinical treatment in HF patients.…”

Table_1_Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.XLSX by Hao Chen (5190)

“…</p>Conclusion<p>This study identified ten energy metabolism-related diagnostic markers using random forest algorithm, which may help optimize risk stratification and clinical treatment in HF patients.…”