EP169/#411  Machine learning method for differential diagnosis and prognosis prediction for early-stage uterine sarcoma using preoperative blood biomarker and age

Yuichi Shoburu; Nozomu Yanaihara; Junya Tabata; Ryoga Nishimura; Miwako Shimazaki; Kazuhiko Oka; Yutaro Kubonoya; Ritsuko Kobayashi-Ogasawara; Rie Honda; Atsuko Yamada; Motoaki Saito; Kyosuke Yamada; Hirokuni Takano; Yasuhisa Terao; Eiryo Kawakami; Aikou Okamoto

doi:10.1136/ijgc-2023-IGCS.259

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AS04. Endometrial/Uterine corpus cancers

EP169/#411 Machine learning method for differential diagnosis and prognosis prediction for early-stage uterine sarcoma using preoperative blood biomarker and age

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Yuichi Shoburu The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Nozomu Yanaihara The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Junya Tabata The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Ryoga Nishimura Yamaguchi University, Faculty of Medicine and Health Sciences, Yamaguchi, Japan RIKEN, Advanced Data Science Project (adsp), Riken Information Randd and Strategy Headquarters, Saitama, Japan PubMed articles Google scholar articles
Miwako Shimazaki The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Kazuhiko Oka The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Yutaro Kubonoya The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Ritsuko Kobayashi-Ogasawara The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Rie Honda The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Atsuko Yamada Juntendo University Faculty of Medicine, Department of Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Motoaki Saito The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Kyosuke Yamada The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Hirokuni Takano The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Yasuhisa Terao Juntendo University Faculty of Medicine, Department of Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles
Eiryo Kawakami RIKEN, Advanced Data Science Project (adsp), Riken Information Randd and Strategy Headquarters, Saitama, Japan Chiba University Graduate School of Medicine, Department of Artificial Intelligence Medicine, Chiba, Japan PubMed articles Google scholar articles
Aikou Okamoto The Jikei University School of Medicine, Obstetrics and Gynecology, Tokyo, Japan PubMed articles Google scholar articles

Citation

Shoburu Y, Yanaihara N, Tabata J, et al

EP169/#411 Machine learning method for differential diagnosis and prognosis prediction for early-stage uterine sarcoma using preoperative blood biomarker and age

International Journal of Gynecologic Cancer 2023;33:A146-A147.

Publication history

First published November 7, 2023.

Online issue publication

November 07, 2023

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