文献
J-GLOBAL ID:202202220205274517
整理番号:22A0977686
直腸癌に対するネオアジュバント化学放射線療法の有効性を予測するためのマルチインスタンス学習に基づくマルチスケール畳込みニューラルネットワークの使用【JST・京大機械翻訳】
Using Multi-Scale Convolutional Neural Network Based on Multi-Instance Learning to Predict the Efficacy of Neoadjuvant Chemoradiotherapy for Rectal Cancer
著者 (9件):
Zhang Dehai
(School of Software, Yunnan University, Kunming, China)
,
Duan Yongchun
(School of Software, Yunnan University, Kunming, China)
,
Guo Jing
(School of Information Science and Engineering, Yunnan University, Kunming, China)
,
Wang Yaowei
(School of Software, Yunnan University, Kunming, China)
,
Yang Yun
(Key Laboratory in Software Engineering of Yunnan Province, School of Software, Yunnan University, Kunming, China)
,
Li Zhenhui
(Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China)
,
Wang Kelong
(School of Software, Yunnan University, Kunming, China)
,
Wu Lin
(Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China)
,
Yu Minghao
(School of Software, Yunnan University, Kunming, China)
資料名:
IEEE Journal of Translational Engineering in Health and Medicine
(IEEE Journal of Translational Engineering in Health and Medicine)
巻:
10
ページ:
ROMBUNNO.4300108.1-8
発行年:
2022年
JST資料番号:
W2440A
ISSN:
2168-2372
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)