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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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Disease Prediction Using Machine Learning on Smartphone-Based Eye, Skin, and Voice Data: Scoping Review

Research Dawadi, Mai Inoue, Jie Ting Tay, Agustin Martin-Morales, Thien Vu, Michihiro Araki

JMIR AI 2025;4:e59094

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An mHealth App to Support Fertility Patients Navigating the World of Infertility (Infotility): Development and Usability Study

Dawadi et al [15] provided a more detailed description of methods and measures. The results of the needs assessment survey showed that most participants had searched the internet for fertility-related information, underscoring the importance of web-based health resources in addressing the informational needs of fertility patients [42]. Moreover, most participants did not report using a fertility mobile app, but the majority were interested in using one [43].

Katya Kruglova, Siobhan Bernadette Laura O'Connell, Shrinkhala Dawadi, Eden Noah Gelgoot, Skye A Miner, Stephanie Robins, Joy Schinazi, Phyllis Zelkowitz