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Katsuhiko Noda

Showing results (1-10 of 8) with videos related to

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Obstetrics & Gynecology Science|December 29, 2020
The application of machine learning for predicting recurrence in patients with early-stage endometrial cancer: a pilot studyMunetoshi Akazawa, Kazunori Hashimoto, Katsuhiko Noda, et al.
Journal of Gynecologic Oncology|January 21, 2024
The automatic diagnosis artificial intelligence system for preoperative magnetic resonance imaging of uterine sarcomaYusuke Toyohara, Kenbun Sone, Katsuhiko Noda, et al.
Scientific Reports|August 2, 2023
Preoperative prediction of sinonasal papilloma by artificial intelligence using nasal video endoscopy: a retrospective studyRyosuke Yui, Masahiro Takahashi, Katsuhiko Noda, et al.
Plos One|October 3, 2022
Preoperative prediction by artificial intelligence for mastoid extension in pars flaccida cholesteatoma using temporal bone high-resolution computed tomography: A retrospective studyMasahiro Takahashi, Katsuhiko Noda, Kaname Yoshida, et al.
Reproductive Medicine and Biology|March 4, 2026
Utilizing Artificial Intelligence in Cine Magnetic Resonance Imaging Analysis: A Promising Approach for Assessment of Uterine Factors and Prediction of Pregnancy Outcomes in Patients With Recurrent Implantation FailureDaiki Hiratsuka, Katsuhiko Noda, Kaname Yoshida, et al.
Journal of Ovarian Research|July 17, 2025
Assessment and prediction models for the quantitative and qualitative reserve of the ovary using machine learningHiroshi Koike, Miyuki Harada, Kaname Yoshida, et al.
Plos One|March 31, 2021
Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopyYu Takahashi, Kenbun Sone, Katsuhiko Noda, et al.
Scientific Reports|November 17, 2022
Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma casesYusuke Toyohara, Kenbun Sone, Katsuhiko Noda, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Obstetrics & Gynecology Science|December 29, 2020
The application of machine learning for predicting recurrence in patients with early-stage endometrial cancer: a pilot studyMunetoshi Akazawa, Kazunori Hashimoto, Katsuhiko Noda, et al.
Journal of Gynecologic Oncology|January 21, 2024
The automatic diagnosis artificial intelligence system for preoperative magnetic resonance imaging of uterine sarcomaYusuke Toyohara, Kenbun Sone, Katsuhiko Noda, et al.
Scientific Reports|August 2, 2023
Preoperative prediction of sinonasal papilloma by artificial intelligence using nasal video endoscopy: a retrospective studyRyosuke Yui, Masahiro Takahashi, Katsuhiko Noda, et al.
Plos One|October 3, 2022
Preoperative prediction by artificial intelligence for mastoid extension in pars flaccida cholesteatoma using temporal bone high-resolution computed tomography: A retrospective studyMasahiro Takahashi, Katsuhiko Noda, Kaname Yoshida, et al.
Reproductive Medicine and Biology|March 4, 2026
Utilizing Artificial Intelligence in Cine Magnetic Resonance Imaging Analysis: A Promising Approach for Assessment of Uterine Factors and Prediction of Pregnancy Outcomes in Patients With Recurrent Implantation FailureDaiki Hiratsuka, Katsuhiko Noda, Kaname Yoshida, et al.
Journal of Ovarian Research|July 17, 2025
Assessment and prediction models for the quantitative and qualitative reserve of the ovary using machine learningHiroshi Koike, Miyuki Harada, Kaname Yoshida, et al.
Plos One|March 31, 2021
Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopyYu Takahashi, Kenbun Sone, Katsuhiko Noda, et al.
Scientific Reports|November 17, 2022
Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma casesYusuke Toyohara, Kenbun Sone, Katsuhiko Noda, et al.
Pageof 1