by Keyword: Relevance
Rubies, C, Batlle, M, Sanz-de la Garza, M, Dantas, AP, Jorba, I, Fernandez, G, Sanguesa, G, Abuli, M, Brugada, J, Sitges, M, Navajas, D, Mont, L, Guasch, E, (2022). Long-Term Strenuous Exercise Promotes Vascular Injury by Selectively Damaging the Tunica Media Experimental Evidence Jacc Basic Transl Sci 7, 681-693 
Moderate exercise has well-founded benefits in cardiovascular health. However, increasing, yet controversial, evidence suggests that extremely trained athletes may not be protected from cardiovascular events as much as moderately trained individuals. In our rodent model, intensive but not moderate training promoted aorta and carotid stiffening and elastic lamina ruptures, tunica media thickening of intramyocardial arteries, and an imbalance between vasoconstrictor and relaxation agents. An up-regulation of angiotensin-converter enzyme, miR-212, miR-132, and miR-146b might account for this deleterious remodeling. Most changes remained after a 4-week detraining. In conclusion, our results suggest that intensive training blunts the benefits of moderate exercise. (C) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.
JTD Keywords: atherosclerosis, cacs, coronary artery calcium score, cad, coronary artery disease, coronary artery disease, cv, cardiovascular, endurance exercise, extreme sport, mmp9, matrix metalloproteinase 9, no, nitric oxide, phe, phenylephrine, vsmc, vascular smooth muscle cell, Age, Atherosclerosis, Cacs, coronary artery calcium score, Cad, coronary artery disease, Coronary artery disease, Coronary atherosclerosis, Cv, cardiovascular, Disease, Endurance exercise, Extreme sport, Metalloproteinases, Micrornas, Mmp9, matrix metalloproteinase 9, No, nitric oxide, Phe, phenylephrine, Physical-activity, Prevalence, Rats, Relevance, Risk, Vascular stiffening, Vsmc, vascular smooth muscle cell
Auffarth, B., Lopez, M., Cerquides, J., (2010). Comparison of redundancy and relevance measures for feature selection in tissue classification of CT images Lecture Notes in Artificial Intelligence 
10th Industrial Conference on Data Mining (ed. Perner, P.), Springer-Verlag Berlin (Berlin, Germany) 6171, 248-262
In this paper we report on a study on feature selection within the minimum-redundancy maximum-relevance framework. Features are ranked by their correlations to the target vector. These relevance scores are then integrated with correlations between features in order to obtain a set of relevant and least-redundant features. Applied measures of correlation or distributional similarity for redunancy and relevance include Kolmogorov-Smirnov (KS) test, Spearman correlations, Jensen-Shannon divergence, and the sign-test. We introduce a metric called "value difference metric" (VDM) and present a simple measure, which we call "fit criterion" (FC). We draw conclusions about the usefulness of different measures. While KS-test and sign-test provided useful information, Spearman correlations are not fit for comparison of data of different measurement intervals. VDM was very good in our experiments as both redundancy and relevance measure. Jensen-Shannon and the sign-test are good redundancy measure alternatives and FC is a good relevance measure alternative.
JTD Keywords: Distributional similarity, Divergence measure, Feature selection, Relevance and redundancy
