[3P] Poster

[I. Cognitive Science, Computational Theories and AI] Neural Network Modeling and Artificial Intelligence

[3P-283] Development of a Machine Learning and Deep Learning-Based Predictive Model for Objective Assessment of Depressive, Euthymic, and Hypomanic States in Bipolar Disorder Using Activity and Sleep Information

*XUE Li^1,3, Goh Onoguchi², Hiroshi Komatsu², Chiaki Ono², Noriko Warita², Zhiqian Yu¹, Atsuko Nagaoka², Sho Horikoshi¹, Kenji Iwabuchi², Kohei Fuji², Yuta Takahashi², Hisashi Ohseto³, Natsuko Kobayashi², Saya Kikuchi², Yasuto Kunii^2,4, Shinichi Kuriyama^3,4, Noriyasu Homma¹, Parashkev Nachev⁵, Akinori ITO⁶, Hiroaki Tomita^1,2,3,4 (1. Graduate School of Medicine, Tohoku University, 2. Tohoku University Hospital, 3. Tohoku University Tohoku Medical Megabank Organization, 4. Tohoku University International Research Institute of Disaster Sciences, 5. UCL Queen Square Institute of Neurology, 6. School of Engineering, Tohoku University)

Keywords:

bipolar disorder,mood,daily information,prediction model

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