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https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/4120
2024-03-28T18:24:24ZComparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods
https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6682
Title: Comparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods
Authors: Choi, Seong Gyu; Oh, Minsuk; Dong Hyuk, Park; Lee, Byeongchan; Lee, Yong-ho; Jee, Sun Ha; Jeon, Justin Y.
Abstract: <jats:title>Abstract</jats:title><jats:p>We compared the prediction performance of machine learning-based undiagnosed diabetes prediction models with that of traditional statistics-based prediction models. We used the 2014–2020 Korean National Health and Nutrition Examination Survey (KNHANES) (N = 32,827). The KNHANES 2014–2018 data were used as training and internal validation sets and the 2019–2020 data as external validation sets. The receiver operating characteristic curve area under the curve (AUC) was used to compare the prediction performance of the machine learning-based and the traditional statistics-based prediction models. Using sex, age, resting heart rate, and waist circumference as features, the machine learning-based model showed a higher AUC (0.788 vs. 0.740) than that of the traditional statistical-based prediction model. Using sex, age, waist circumference, family history of diabetes, hypertension, alcohol consumption, and smoking status as features, the machine learning-based prediction model showed a higher AUC (0.802 vs. 0.759) than the traditional statistical-based prediction model. The machine learning-based prediction model using features for maximum prediction performance showed a higher AUC (0.819 vs. 0.765) than the traditional statistical-based prediction model. Machine learning-based prediction models using anthropometric and lifestyle measurements may outperform the traditional statistics-based prediction models in predicting undiagnosed diabetes.</jats:p>2023-08-01T00:00:00ZPrognostic value of resting heart rate in predicting undiagnosed diabetes in adults: Korean National Health and Nutrition Examination Survey 2008–2018
https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6428
Title: Prognostic value of resting heart rate in predicting undiagnosed diabetes in adults: Korean National Health and Nutrition Examination Survey 2008–2018
Authors: Park, Dong-Hyuk; Goo, Seon Young; Hong, Sung Hyun; Min, Ji-hee; Byeon, Ji Yong; Lee, Mi-Kyung; Lee, Hae Dong; Ahn, Byoung Wook; Kimm, Heejin; Jee, Sun Ha; Lee, Dong Hoon; Lee, Yong-ho; Kang, Eun Seok; Jeon, Justin Y.2023-01-01T00:00:00Z요통 환자의 보행 특성에 관한 체계적 문헌고찰 연구
https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6527
Title: 요통 환자의 보행 특성에 관한 체계적 문헌고찰 연구
Authors: 이종현; 윤용진20221007-01-01T00:00:00ZA Systematic review and Meta-Analysis of the Effect of Exercise with or Without Concurrent Joint Mobilization on Adhesive Capsulitis of the Shoulder
https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6536
Title: A Systematic review and Meta-Analysis of the Effect of Exercise with or Without Concurrent Joint Mobilization on Adhesive Capsulitis of the Shoulder
Authors: 이종현; 전형규; 윤용진20220422-01-01T00:00:00Z