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Skip search results from other journals and go to results- 4 JMIR Medical Informatics
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
Zhiwei Gao, Sumio Fujita, Nobuyuki Shimizu, Kongmeng Liew, Taichi Murayama, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
JMIR Public Health Surveill 2021;7(7):e29865Download Citation: END BibTex RIS

Satoshi Nishioka, Satoshi Watabe, Yuki Yanagisawa, Kyoko Sayama, Hayato Kizaki, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori
J Med Internet Res 2024;26:e55794Download Citation: END BibTex RIS

Tomohiro Nishiyama, Shuntaro Yada, Shoko Wakamiya, Satoko Hori, Eiji Aramaki
J Med Internet Res 2023;25:e44870Download Citation: END BibTex RIS

Tomohiro Nishiyama, Ayane Yamaguchi, Peitao Han, Lis Weiji Kanashiro Pereira, Yuka Otsuki, Gabriel Herman Bernardim Andrade, Noriko Kudo, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki, Masahiro Takada, Masakazu Toi
JMIR Med Inform 2024;12:e58977Download Citation: END BibTex RIS

Genta Ito, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
JMIR Form Res 2024;8:e54044Download Citation: END BibTex RIS

Zhouqing Zhang, Kongmeng Liew, Roeline Kuijer, Wan Jou She, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
JMIR Cancer 2024;10:e51332Download Citation: END BibTex RIS

Tomomi Watanabe, Shuntaro Yada, Eiji Aramaki, Hiroshi Yajima, Hayato Kizaki, Satoko Hori
JMIR Cancer 2022;8(2):e37840Download Citation: END BibTex RIS

Identification of Adverse Drug Event–Related Japanese Articles: Natural Language Processing Analysis
Shogo Ujiie, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki
JMIR Med Inform 2020;8(11):e22661Download Citation: END BibTex RIS

Kazuya Taira, Takahiro Itaya, Shuntaro Yada, Kirara Hiyama, Ayame Hanada
JMIR Nursing 2025;8:e67197Download Citation: END BibTex RIS

Takuya Fukushima, Masae Manabe, Shuntaro Yada, Shoko Wakamiya, Akiko Yoshida, Yusaku Urakawa, Akiko Maeda, Shigeyuki Kan, Masayo Takahashi, Eiji Aramaki
JMIR Med Inform 2025;13:e65047Download Citation: END BibTex RIS