Design of a Clinical Decision Support System for Predicting Erectile Dysfunction in Men Using NHIRD Dataset

Erectile dysfunction (ED) affects millions of men worldwide. Men with ED generally complain failure to attain or maintain an adequate erection during sexual activity. The prevalence of ED is strongly correlated with age, affecting about 40% of men at age 40 and nearly 70% at age 70. A variety of chr...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2019-09, Vol.23 (5), p.2127-2137
Hauptverfasser:	Chen, Yung-Fu, Lin, Chih-Sheng, Hong, Chun-Fu, Lee, Dah-Jye, Sun, Changming, Lin, Hsuan-Hung
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Age Aged Algorithms Apnea Cardiovascular diseases clinical decision support system (CDSS) Comorbidity Congestive heart failure Construction Coronary artery disease Databases, Factual Decision support systems Decision Support Systems, Clinical Diabetes Diabetes mellitus Diseases Erectile dysfunction Erectile dysfunction (ED) Erectile Dysfunction - diagnosis genetic algorithm (GA) Genetic algorithms Gout Heart Heart diseases Humans Hypertension Indexes Ischemia Male Middle Aged National Health Insurance Research Database (NHIRD) Performance prediction Prediction models Prostate Renal failure Sleep Sleep apnea Sleep disorders Support Vector Machine support vector machine (SVM) Support vector machines Training Young Adult
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