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Predicting Increased Blood Pressure Using Machine Learning
Joint Authors
Golino, Hudson Fernandes
Amaral, Liliany Souza de Brito
Duarte, Stenio Fernando Pimentel
Gomes, Cristiano Mauro Assis
Soares, Telma de Jesus
Reis, Luciana Araujo dos
Santos, Joselito
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The present study investigates the prediction of increased blood pressure by body mass index (BMI), waist (WC) and hip circumference (HC), and waist hip ratio (WHR) using a machine learning technique named classification tree.
Data were collected from 400 college students (56.3% women) from 16 to 63 years old.
Fifteen trees were calculated in the training group for each sex, using different numbers and combinations of predictors.
The result shows that for women BMI, WC, and WHR are the combination that produces the best prediction, since it has the lowest deviance (87.42), misclassification (.19), and the higher pseudo R 2 (.43).
This model presented a sensitivity of 80.86% and specificity of 81.22% in the training set and, respectively, 45.65% and 65.15% in the test sample.
For men BMI, WC, HC, and WHC showed the best prediction with the lowest deviance (57.25), misclassification (.16), and the higher pseudo R 2 (.46).
This model had a sensitivity of 72% and specificity of 86.25% in the training set and, respectively, 58.38% and 69.70% in the test set.
Finally, the result from the classification tree analysis was compared with traditional logistic regression, indicating that the former outperformed the latter in terms of predictive power.
American Psychological Association (APA)
Golino, Hudson Fernandes& Amaral, Liliany Souza de Brito& Duarte, Stenio Fernando Pimentel& Gomes, Cristiano Mauro Assis& Soares, Telma de Jesus& Reis, Luciana Araujo dos…[et al.]. 2014. Predicting Increased Blood Pressure Using Machine Learning. Journal of Obesity،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1042374
Modern Language Association (MLA)
Golino, Hudson Fernandes…[et al.]. Predicting Increased Blood Pressure Using Machine Learning. Journal of Obesity No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1042374
American Medical Association (AMA)
Golino, Hudson Fernandes& Amaral, Liliany Souza de Brito& Duarte, Stenio Fernando Pimentel& Gomes, Cristiano Mauro Assis& Soares, Telma de Jesus& Reis, Luciana Araujo dos…[et al.]. Predicting Increased Blood Pressure Using Machine Learning. Journal of Obesity. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1042374
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1042374