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The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.
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Ph.D in Applied Statistics, AgroParisTech, France, 2013. From 2014, I'm working at Affiliated Zhongshan Hospital of Dalian University as a Research Fellow. My principal research areas are Bayesian methods (especially Bayesian Networks modeling) applied in clinical setting.
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Body composition prediction by multivariate statistical modeling
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response. 200 pp. Englisch. Codice articolo 9783639862157
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tian SimiaoPh.D in Applied Statistics, AgroParisTech, France, 2013. From 2014, I m working at Affiliated Zhongshan Hospital of Dalian University as a Research Fellow. My principal research areas are Bayesian methods (especially Bayes. Codice articolo 151404851
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response. Codice articolo 9783639862157
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paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA80036398621556
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Body composition prediction by multivariate statistical modeling
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Scholars' Press Jan 2016, 2016
ISBN 10: 3639862155
ISBN 13: 9783639862157
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 200 pp. Englisch. Codice articolo 9783639862157
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Taschenbuch. Condizione: Neu. Body composition prediction by multivariate statistical modeling | Simiao Tian | Taschenbuch | 200 S. | Englisch | 2016 | Scholars' Press | EAN 9783639862157 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 104023954
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