Exploring the Feasibility of Insomnia Subtyping using Machine Learning Clustering based on Digital Phenotype Data

Chul-Hyun Cho

[P296] Exploring the Feasibility of Insomnia Subtyping using Machine Learning Clustering based on Digital Phenotype Data

*Chul-Hyun Cho^1,2, Yoonseo Jeon¹, Jingyeong Jeong¹, Hyungju Kim³, Taesu Cheong³, Ji Won Yeom¹, Heon-Jeong Lee¹ (1. Department of Psychiatry, Korea University College of Medicine, Seoul, Korea, 2. Department of Biomedical Informatics, Korea University College of Medicine, Seoul, Korea, 3. Department of Industrial Management Engineering, Korea University Graduate School, Seoul, Korea)

Keywords:Insomnia, Digital Phenotyping, Machine Learning

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Sleep Disorders

[P296] Exploring the Feasibility of Insomnia Subtyping using Machine Learning Clustering based on Digital Phenotype Data

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