Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Uchino, Eiichiro"'
Out-of-distribution Reject Option Method for Dataset Shift Problem in Early Disease Onset Prediction
Autor:
Tosaki, Taisei, Uchino, Eiichiro, Kojima, Ryosuke, Mineharu, Yohei, Arita, Mikio, Miyai, Nobuyuki, Tamada, Yoshinori, Mikami, Tatsuya, Murashita, Koichi, Nakaji, Shigeyuki, Okuno, Yasushi
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, the prediction effectiveness is hindered by dataset shift, which involves discrepancies in data distribution between the training
Externí odkaz:
http://arxiv.org/abs/2405.19864
Autor:
Nakamura, Aya, Kojima, Ryosuke, Okamoto, Yuji, Uchino, Eiichiro, Mineharu, Yohei, Harada, Yohei, Kamada, Mayumi, Muto, Manabu, Yanagita, Motoko, Okuno, Yasushi
Many diseases, including cancer and chronic conditions, require extended treatment periods and long-term strategies. Machine learning and AI research focusing on electronic health records (EHRs) have emerged to address this need. Effective treatment
Externí odkaz:
http://arxiv.org/abs/2307.11487
Autor:
Uchino, Eiichiro
乙第13440号
論医博第2239号
新制||医||1054(附属図書館)
学位規則第4条第2項該当
Doctor of Medical Science
Kyoto University
DFAM
論医博第2239号
新制||医||1054(附属図書館)
学位規則第4条第2項該当
Doctor of Medical Science
Kyoto University
DFAM
Externí odkaz:
http://hdl.handle.net/2433/265964
Autor:
Nakamura, Kazuki, Uchino, Eiichiro, Sato, Noriaki, Araki, Ayano, Terayama, Kei, Kojima, Ryosuke, Murashita, Koichi, Itoh, Ken, Mikami, Tatsuya, Tamada, Yoshinori, Okuno, Yasushi
Early disease detection and prevention methods based on effective interventions are gaining attention. Machine learning technology has enabled precise disease prediction by capturing individual differences in multivariate data. Progress in precision
Externí odkaz:
http://arxiv.org/abs/2205.15598
Autor:
Sakuragi, Minoru1,2 (AUTHOR), Uchino, Eiichiro1,2 (AUTHOR), Sato, Noriaki1,2 (AUTHOR), Matsubara, Takeshi2 (AUTHOR), Ueda, Akihiko1,3 (AUTHOR), Mineharu, Yohei1,4,5 (AUTHOR), Kojima, Ryosuke1 (AUTHOR), Yanagita, Motoko2,6 (AUTHOR) okuno.yasushi.4c@kyoto-u.ac.jp, Okuno, Yasushi1 (AUTHOR) okuno.yasushi.4c@kyoto-u.ac.jp
Publikováno v:
PLoS ONE. 3/19/2024, Vol. 19 Issue 3, p1-14. 14p.
Autor:
Nakamura, Kazuki, Kojima, Ryosuke, Uchino, Eiichiro, Murashita, Koichi, Itoh, Ken, Nakaji, Shigeyuki, Okuno, Yasushi
Clinical decision making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information. However, t
Externí odkaz:
http://arxiv.org/abs/2010.16087
Autor:
Nakamura, Kazuki, Uchino, Eiichiro, Sato, Noriaki, Araki, Ayano, Terayama, Kei, Kojima, Ryosuke, Murashita, Koichi, Itoh, Ken, Mikami, Tatsuya, Tamada, Yoshinori, Okuno, Yasushi
Publikováno v:
In Journal of Biomedical Informatics August 2023 144
Autor:
Kaneko, Keiichi, Sato, Yuki, Uchino, Eiichiro, Toriu, Naoya, Shigeta, Mayo, Kiyonari, Hiroshi, Endo, Shuichiro, Fukuma, Shingo, Yanagita, Motoko
Publikováno v:
In Kidney International August 2022 102(2):280-292
Akademický článek
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Autor:
Sato, Noriaki, Uchino, Eiichiro, Kojima, Ryosuke, Sakuragi, Minoru, Hiragi, Shusuke, Minamiguchi, Sachiko, Haga, Hironori, Yokoi, Hideki, Yanagita, Motoko, Okuno, Yasushi
Publikováno v:
In Kidney International Reports September 2021 6(9):2445-2454