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Machine Learning for Predicting Postoperative Functional Disability and Mortality Among Older Patients With Cancer: Retrospective Cohort Study

Yuki Hashimoto, Norihiko Inoue, Takuaki Tani, Shinobu Imai

JMIR Aging 2025;8:e65898

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Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population–Based Study

Thien Vu, Yoshihiro Kokubo, Mai Inoue, Masaki Yamamoto, Attayeb Mohsen, Agustin Martin-Morales, Research Dawadi, Takao Inoue, Jie Ting Tay, Mari Yoshizaki, Naoki Watanabe, Yuki Kuriya, Chisa Matsumoto, Ahmed Arafa, Yoko M Nakao, Yuka Kato, Masayuki Teramoto, Michihiro Araki

JMIR Cardio 2025;9:e68066

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Efficacy of a Personalized Mobile Health Intervention (BedTime) to Increase Sleep Duration Among Short-Sleeping Patients With Type 2 Diabetes: Protocol for a Pilot Randomized Controlled Trial

Yuki Ban, Kayo Waki, Ryohei Nakada, Akihiro Isogawa, Kengo Miyoshi, Hironori Waki, Shunsuke Kato, Hideaki Sawaki, Takashi Murata, Yushi Hirota, Shuichiro Saito, Seiji Nishikage, Atsuhito Tone, Mayumi Seno, Masao Toyoda, Shinichi Kajino, Kazuki Yokota, Yuya Tsurutani, Toshimasa Yamauchi, Masaomi Nangaku, Kazuhiko Ohe

JMIR Res Protoc 2025;14:e64023

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Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation

Tatsuki Hasegawa, Hayato Kizaki, Keisho Ikegami, Shungo Imai, Yuki Yanagisawa, Shuntaro Yada, Eiji Aramaki, Satoko Hori

JMIR Med Inform 2025;13:e65371

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Identifying Adverse Events in Outpatients With Prostate Cancer Using Pharmaceutical Care Records in Community Pharmacies: Application of Named Entity Recognition

Yuki Yanagisawa, Satoshi Watabe, Sakura Yokoyama, Kyoko Sayama, Hayato Kizaki, Masami Tsuchiya, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori

JMIR Cancer 2025;11:e69663

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Effectiveness of a Videoconference-Based Cognitive Behavioral Therapy Program for Patients with Schizophrenia: Pilot Randomized Controlled Trial

Masayuki Katsushima, Hideki Nakamura, Yuki Shiko, Hideki Hanaoka, Eiji Shimizu

JMIR Form Res 2025;9:e59540

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Predictive Factors and the Predictive Scoring System for Falls in Acute Care Inpatients: Retrospective Cohort Study

Chihiro Saito, Eiji Nakatani, Hatoko Sasaki, Naoko E Katsuki, Masaki Tago, Kiyoshi Harada

JMIR Hum Factors 2025;12:e58073

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Validation of Sleep Measurements of an Actigraphy Watch: Instrument Validation Study

Mari Waki, Ryohei Nakada, Kayo Waki, Yuki Ban, Ryo Suzuki, Toshimasa Yamauchi, Masaomi Nangaku, Kazuhiko Ohe

JMIR Form Res 2025;9:e63529

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Quantifying the Regional Disproportionality of COVID-19 Spread: Modeling Study

This finding aligns with previous research by Ikeda, Sasaki, and Nakano [7]. The following examples provide interesting insights; when the Theil index value was high and the number of confirmed cases was low (d=60, 550, etc), it indicated that the infectious disease was localized and beginning to spread to various regions.

Kenji Sasaki, Yoichi Ikeda, Takashi Nakano

JMIR Form Res 2025;9:e59230

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