Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-022-08780-w.pdf
Reference36 articles.
1. Bracigliano A, Tatangelo F, Perri F et al (2021) Malignant sinonasal tumors: update on histological and clinical management. Curr Oncol 28:2420–2438
2. Raghavan P, Phillips CD (2007) Magnetic resonance imaging of sinonasal malignancies. Top Magn Reson Imaging 18:259–267
3. Resto VA, Deschler DG (2004) Sinonasal malignancies. Otolaryngol Clin North Am 37:473–487
4. Day TA, Beas RA, Schlosser RJ et al (2005) Management of paranasal sinus malignancy. Curr Treat Options Oncol 6:3–18
5. Mody MD, Saba NF (2020) Multimodal therapy for sinonasal malignancies: updates and review of current treatment. Curr Treat Options Oncol 21:4
Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. MRI-based radiomics signatures for preoperative prediction of Ki-67 index in primary central nervous system lymphoma;European Journal of Radiology;2024-09
2. Development and validation of a prediction model for malignant sinonasal tumors based on MR radiomics and machine learning;European Radiology;2024-08-30
3. Radiomics nomogram based on CT radiomics features and clinical factors for prediction of Ki-67 expression and prognosis in clear cell renal cell carcinoma: a two-center study;Cancer Imaging;2024-08-06
4. Multiparametric MRI-based radiomics approach with deep transfer learning for preoperative prediction of Ki-67 status in sinonasal squamous cell carcinoma;Frontiers in Oncology;2024-06-13
5. Prediction of the Ki-67 expression level in head and neck squamous cell carcinoma with machine learning-based multiparametric MRI radiomics: a multicenter study;BMC Cancer;2024-04-05
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
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3