Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine

• Published in: International journal of environmental research and public health Vol. 16; no. 21; p. 4269
• Main Author: Byeon, Haewon
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 03.11.2019; MDPI
• Subjects: Aged; Aged, 80 and over; Algorithms; Cognitive ability; Cross-Sectional Studies; Deglutition; Deglutition Disorders - psychology; Dentures; Dysphagia; Elementary schools; Female; Gender; Health care; Humans; Male; Mental depression; Older people; Quality; Quality of Life; Republic of Korea; Risk factors; Sociodemographics; Studies; Support Vector Machine; Variables; Republic of Korea; dysphagia; elderly living in a local community; support vector machine; swallowing quality-of-life; risk factor

Background and Objectives: This study developed a support vector machine (SVM) algorithm-based prediction model with considering influence factors associated with the swallowing quality-of-life as the predictor variables and provided baseline information for enhancing the swallowing quality of elder...