A Prediction Model for Benign Laryngeal Disease Using Supervised Learning Techniques
| Autor: | Sung-Hyoun Cho, Haewon Byeon, Seong-Hun Yu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
Artificial neural network National Health and Nutrition Examination Survey business.industry 020209 energy Supervised learning Biomedical Engineering Binge drinking Bioengineering 02 engineering and technology Audiology Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Voice problem medicine 020201 artificial intelligence & image processing Significant risk Artificial neural network algorithm business Biotechnology Laryngeal disease Clinical psychology |
| Zdroj: | International Journal of Bio-Science and Bio-Technology. 8:105-110 |
| ISSN: | 2233-7849 |
| DOI: | 10.14257/ijbsbt.2016.8.4.12 |
| Popis: | This study developed prediction model for benign laryngeal disease based on machine learning which reflects the characteristics of Korean adults. This study analyzed 8,713 adults (3,801 males and 4,912 females) over the age of 19 who completed laryngoscopic assessment of 2010-2012 Korea National Health and Nutrition Examination Survey (KNHNES). RBF artificial neural network algorithm was used for analysis. The explanatory variables were age, gender, educational level, occupation, income, smoking, binge drinking, and self-reported voice problem. As the result of construction of prediction model for benign laryngeal disease, self-reported voice problem, educational level, income and smoking were significant risk factors of benign laryngeal disease (p |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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