Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima, Naoki Nakashima, “Explanation of Machine Learning Models Using Shapley Additive Explanation and Application for Real Data in Hospital”, Computer Methods and Programs in Biomedicine, Vol. 214, Article 106584, https://doi.org/10.1016/j.cmpb.2021.106584, Feb. 2022
Takanori Yamashita, Yoshifumi Wakata, Hideki Nakaguma, Yasunobu Nohara, Shinj Hato, Susumu Kawamura, Shuko Muraoka, Masatoshi Sugita, Mihoko Okada, Naoki Nakashima, Hidehisa Soejima, “Machine Learning for Classification of Postoperative Patient Status Using Standardized Medical Data”, Computer Methods and Programs in Biomedicine, Vol. 214, Article 106583, https://doi.org/10.1016/j.cmpb.2021.106583, Feb. 2022
Kimiyo Kikuchi, Yoko Sato, Rieko Izukura, Mariko Nishikitani, Kiyoko Kato, Seiichi Morokuma, Meherun Nessa, Yasunobu Nohara, Fumihiko Yokota, Ashir Ahmed, Rafiqul Islam Maruf, Naoki Nakashima, “Portable Health Clinic for Sustainable Care of Mothers and Newborns in Rural Bangladesh”, Computer Methods and Programs in Biomedicine, Vol. 207, https://doi.org/10.1016/j.cmpb.2021.106156, Aug. 2021
Toyoshi Inoguchi, Yasunobu Nohara, Chinatsu Nojiri and Naoki Nakashima, “Association of serum bilirubin levels with risk of cancer development and total death”, Scientific Reports, Vol. 11, Article No. 13224, https://doi.org/10.1038/s41598-021-92442-2, Jul. 2021
Hidehisa Soejima, Koutarou Matsumoto, Naoki Nakashima, Yasunobu Nohara, Takanori Yamashita, Jiro Machida, Hideki Nakaguma, “A functional learning health system in Japan: Experience with processes and information infrastructure toward continuous health improvement”, Learn Health Sys. 2020; e10252. https://doi.org/10.1002/lrh2.10252, pp.1-12, Nov. 2020
Koutarou Matsumoto, Yasunobu Nohara, Hidehisa Soejima, Toshiro Yonehara, Naoki Nakashima, Masahiro Kamouchi, “Stroke Prognostic Scores and Data-Driven Prediction of Clinical Outcomes After Acute Ischemic Stroke”, Stroke, Vol.51, No.5, https://doi.org/10.1161/STROKEAHA.119.027300, pp. 1477 – 1483, May 2020.
International Confrence
Yasunobu Nohara, “Maximizing Accuracy of Shapley Additive Explanations with Limited Features — A Quantification of Explanation Fidelity and Trade-off Between Fidelity and Number of Features”, IJCAI 2024 Workshop on Explainable Artificial Intelligence (XAI2024), Aug. 2024
Koutarou Matsumoto, Yasunobu Nohara, Mikako Sakaguchi, Yohei Takayama, Takanori Yamashita, Hidehisa Soejima, Naoki Nakashima, “Development of Machine Learning Prediction Models for Self-Extubation After Delirium Using Emergency Department Data.”, Studies in Health Technology and Informatics (MedInfo2023), Vol. 310, pp.1001-1005, https://doi.org/10.3233/shti231115, Jan. 2024