共 50 条
- [31] Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic reviewEUROPEAN JOURNAL OF RADIOLOGY, 2019, 121Granzier, R. W. Y.van Nijnatten, T. J. A.Woodruff, H. C.Smidt, M. L.Lobbes, M. B., I
- [32] Multiparametric MRI-based radiomics analysis: differentiation of subtypes of cervical cancer in the early stageACTA RADIOLOGICA, 2022, 63 (06) : 847 - 856Wang, WeiJiao, YiNingZhang, LiChiFu, CaixiaZhu, XiaoLiWang, QianGu, Yajia
- [33] MRI-based radiomics models can improve prognosis prediction for nasopharyngeal carcinoma with neoadjuvant chemotherapyMAGNETIC RESONANCE IMAGING, 2022, 88 : 108 - 115Zeng, FanLin, Kai-RongJin, Ya-BinLi, Hao-JiangQuan, QiangSu, Jian-ChunChen, KaiZhang, JingHan, ChenZhang, Guo-Yi
- [34] MRI-Based Prediction of Recurrence-Free Survival in Breast Cancer Patients Early On in Neoadjuvant ChemotherapyMEDICAL PHYSICS, 2017, 44 (06)Drukker, K.Li, H.Antropova, N.Edwards, A.Papaioannou, J.Giger, M.
- [35] Development of a MRI-Based Radiomics Nomogram for Prediction of Response of Patients With Muscle-Invasive Bladder Cancer to Neoadjuvant ChemotherapyFRONTIERS IN ONCOLOGY, 2022, 12Zhang, XinxinWang, YichenZhang, JinZhang, LianyuWang, SicongChen, Yan
- [36] Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 ChallengeRADIOLOGY-IMAGING CANCER, 2024, 6 (01):Li, WenPartridge, Savannah C.Newitt, David C.Steingrimsson, JonMarques, Helga S.Bolan, Patrick J.Hirano, MichaelBearce, Benjamin AaronKalpathy-Cramer, JayashreeBoss, Michael A.Teng, XinzhiZhang, JiangCai, JingKontos, DespinaCohen, Eric A.Mankowski, Walter C.Liu, MichaelHa, RichardPellicer-Valero, Oscar J.Maier-Hein, KlausRabinovici-Cohen, SimonaTlusty, TalOzery-Flato, MichalParekh, Vishwa S.Jacobs, Michael A.Yan, RanSung, KyunghyunKazerouni, Anum S.Dicarlo, Julie C.Yankeelov, Thomas E.Chenevert, Thomas L.Hylton, Nola M.
- [37] Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast CancerFRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2021, 9Huang, YuhongChen, WenbenZhang, XiaolingHe, ShaofuShao, NanShi, HuijuanLin, ZhenzheWu, XuetingLi, TongkengLin, HaotianLin, Ying
- [38] Prediction of early clinical response to neoadjuvant chemotherapy in Triple-negative breast cancer: Incorporating Radiomics through breast MRISCIENTIFIC REPORTS, 2024, 14 (01):Lee, Hyo-jaeLee, Jeong HoonLee, Jong EunNa, Yong MinPark, Min HoLee, Ji ShinLim, Hyo Soon
- [39] MRI-Based Radiomics Features to Predict Treatment Response to Neoadjuvant Chemotherapy in Locally Advanced Rectal Cancer: A Single Center, Prospective StudyFRONTIERS IN ONCOLOGY, 2022, 12Chen, Bi-YunXie, HuiLi, YuanJiang, Xin-HuaXiong, LangTang, Xiao-FengLin, Xiao-FengLi, LiCai, Pei-Qiang
- [40] Radiomics of MRI for the Prediction of the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer Patients: A Single Referral Centre AnalysisCANCERS, 2021, 13 (17)Pesapane, FilippoRotili, AnnaBotta, FrancescaRaimondi, SaraBianchini, LindaCorso, FedericaFerrari, FedericaPenco, SilviaNicosia, LucaBozzini, AnnaPizzamiglio, MariaOriggi, DanielaCremonesi, MartaCassano, Enrico