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Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset

More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The a...

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Autores principales: Chen, Yung-Fu, Lin, Chih-Sheng, Wang, Kuo-An, Rahman, La Ode Abdul, Lee, Dah-Jye, Chung, Wei-Sheng, Lin, Hsuan-Hung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885339/
https://www.ncbi.nlm.nih.gov/pubmed/29765586
http://dx.doi.org/10.1155/2018/9621640
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author Chen, Yung-Fu
Lin, Chih-Sheng
Wang, Kuo-An
Rahman, La Ode Abdul
Lee, Dah-Jye
Chung, Wei-Sheng
Lin, Hsuan-Hung
author_facet Chen, Yung-Fu
Lin, Chih-Sheng
Wang, Kuo-An
Rahman, La Ode Abdul
Lee, Dah-Jye
Chung, Wei-Sheng
Lin, Hsuan-Hung
author_sort Chen, Yung-Fu
collection PubMed
description More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD). After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7%) were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration) were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs) were designed with integrated genetic algorithm (GA) and support vector machine (SVM) by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and OCS therapies should be continuously monitored, especially for patients with older age and women after menopause, to prevent from exceeding the maximum dosage.
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spelling pubmed-58853392018-05-14 Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset Chen, Yung-Fu Lin, Chih-Sheng Wang, Kuo-An Rahman, La Ode Abdul Lee, Dah-Jye Chung, Wei-Sheng Lin, Hsuan-Hung J Healthc Eng Research Article More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD). After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7%) were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration) were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs) were designed with integrated genetic algorithm (GA) and support vector machine (SVM) by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and OCS therapies should be continuously monitored, especially for patients with older age and women after menopause, to prevent from exceeding the maximum dosage. Hindawi 2018-03-22 /pmc/articles/PMC5885339/ /pubmed/29765586 http://dx.doi.org/10.1155/2018/9621640 Text en Copyright © 2018 Yung-Fu Chen et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Yung-Fu
Lin, Chih-Sheng
Wang, Kuo-An
Rahman, La Ode Abdul
Lee, Dah-Jye
Chung, Wei-Sheng
Lin, Hsuan-Hung
Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title_full Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title_fullStr Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title_full_unstemmed Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title_short Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset
title_sort design of a clinical decision support system for fracture prediction using imbalanced dataset
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5885339/
https://www.ncbi.nlm.nih.gov/pubmed/29765586
http://dx.doi.org/10.1155/2018/9621640
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