Earticle

초록

영어

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<0.05).Construction of prevention model is required to be constructed based on this model to minimize the risks of benign laryngeal disease in Koreans.

목차

Abstract
 1. Introduction
 2. Methods
  2.1 Data Source
  2.2 Measurements
  2.3 Artificial neural network
 3. Results
  3.1 General Characteristics of Subjects
  3.2. RBF Artificial Neural Network Analysis
 4. Conclusions
 References

키워드

저자

• Sunghyoun Cho [ Dept. of Physical Therapy, Nambu University, Gwangju, South Korea ]
• Seonghun Yu [ Dept. of Physical Therapy, Gwng-ju Trauma Center, Gwangju, South Korea ]
• Haewon Byeon [ Dept. of Speech Language Pathology & Audiology, Nambu University, Gwangju, South Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605