MRI-based radiomics model to preoperatively predict mesenchymal transition subtype in high-grade serous ovarian cancer-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

MRI-based radiomics model to preoperatively predict mesenchymal transition subtype in high-grade serous ovarian cancer

Published:2024-05 Issue:5 Volume:79 Page:e715-e724
ISSN:0009-9260
Container-title:Clinical Radiology
language:en
Short-container-title:Clinical Radiology

Author:

Lin Z.,Ge H.,Guo Q.,Ren J.,Gu W.,Lu J.,Zhong Y.,Qiang J.,Gong J.,Li H.

Funder

Science and Technology Commission of Shanghai Municipality

China International Medical Foundation

GE Healthcare

National Natural Science Foundation of China

Natural Science Foundation of Shanghai Municipality

Publisher

Elsevier BV

Reference41 articles.

1. Cancer statistics, 2022;Siegel;CA Cancer J Clin,2022

2. Cancer statistics in China and United States, 2022: profiles, trends, and determinants;Xia;Chin Med J (Engl),2022

3. Prognostic gene expression signature for high-grade serous ovarian cancer;Millstein;Ann Oncol,2020

4. Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer;Boehm;Nat Cancer,2022

5. Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer;Konecny;J Natl Cancer Inst,2014

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP