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BMC Public Health|May 7, 2024
Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approachSaida Salima Nawrin, Hitoshi Inada, Haruki Momma, et al.Journal of Activity, Sedentary and Sleep Behaviors|April 11, 2025
Examining physical activity clustering using machine learning revealed a diversity of 24-hour step-counting patternsSaida Salima Nawrin, Hitoshi Inada, Haruki Momma, et al.Frontiers in Physiology|October 1, 2021
Low Back Pain Exacerbation Is Predictable Through Motif Identification in Center of Pressure Time Series Recorded During Dynamic SittingZiheng Wang, Keizo Sato, Saida Salima Nawrin, et al.European Journal of Nutrition|February 25, 2024
Dietary patterns associated with the incidence of hypertension among adult Japanese males: application of machine learning to a cohort studyLongfei Li, Haruki Momma, Haili Chen, et al.Frontiers in Nutrition|December 12, 2025
Dietary patterns and obesity are associated with type 2 diabetes risk in elderly Chinese men: a machine learning approachHaowei Sun, Lijin Zhu, Peng Wang, et al.Pageof 1