1.A Prediction Model for Mild Cognitive Impairment Using Random Forests

作　　者：Haewon Byeon

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2015 ;6(12).doi:10.14569/IJACSA.2015.061202

出版社：Science and Information Society (SAI)

文章 ID：172191140

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2.A Feature Analysis of Risk Factors for Stroke in the Middle-Aged Adults

作　　者：Haewon Byeon ;Hyeung Woo Koh

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2015 ;6(12).doi:10.14569/IJACSA.2015.061213

出版社：Science and Information Society (SAI)

文章 ID：172191160

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3.Assessment for the Model Predicting of the Cognitive and Language Ability in the Mild Dementia by the Method of Data-Mining Technique

作　　者：Haewon Byeon ;Dongwoo Lee ;Sunghyoun Cho

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2016 ;7(6).doi:10.14569/IJACSA.2016.070609

出版社：Science and Information Society (SAI)

文章 ID：181031773

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4.Development of Prediction Model for Endocrine Disorders in the Korean Elderly Using CART Algorithm

作　　者：Haewon Byeon

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2015 ;6(9).doi:10.14569/IJACSA.2015.060916

出版社：Science and Information Society (SAI)

文章 ID：111492006

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5.The Factors of Subjective Voice Disorder Using Integrated Method of Decision Tree and Multi-Layer Perceptron Artificial Neural Network Algorithm

作　　者：Haewon Byeon ;Sunghyoun Cho

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2016 ;7(5).doi:10.14569/IJACSA.2016.070517

出版社：Science and Information Society (SAI)

文章 ID：179487202

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6.Exploring Factors Associated with Voucher Program for Speech Language Therapy for the Preschoolers of Parents with Communication Disorder using Weighted Random Forests

作　　者：Haewon Byeon ;Sulki Cha ;KyoungYuel Lim

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2019 ;10(5):12-17.doi:10.14569/IJACSA.2019.0100503

出版社：Science and Information Society (SAI)

文章 ID：238921226

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7.Evaluating Factors for Predicting the Life Dissatisfaction of South Korean Elderly using Soft Margin Support Vector Machine based on Communication Frequency, Social Network Health Behavior and Depression

作　　者：Haewon Byeon ;Seong-Tae Kim

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2019 ;10(9):392-398.

出版社：Science and Information Society (SAI)

文章 ID：243743054

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8.Chi-Square Automatic Interaction Detection Modeling for Predicting Depression in Multicultural Female Students

作　　者：Haewon Byeon

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2017 ;8(12).doi:10.14569/IJACSA.2017.081222

出版社：Science and Information Society (SAI)

文章 ID：210682438

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9.Exploring the Predictors of Rapid Eye Movement Sleep Behavior Disorder for Parkinson’s Disease Patients Using Classifier Ensemble

作　　者：Haewon Byeon

出　　处：Healthcare. 2020 ;8(2):121-134.doi:10.3390/healthcare8020121

出版社：MDPI Publishing

文章 ID：257051951

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10.Development Trends of Online-based Aural Rehabilitation Programs for Children with Cochlear Implant Coping with the Fourth Industrial Revolution and Implication in Speech-Language Pathology

作　　者：Haewon Byeon

出　　处：International Journal of Advanced Computer Science and Applications(IJACSA). 2019 ;10(10).doi:10.14569/IJACSA.2019.0101005

出版社：Science and Information Society (SAI)

文章 ID：256031541

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	International Journal of Advanced Computer Science and Applications(IJACSA)	26篇
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