289 related articles for article (PubMed ID: 29970244)
1. Breast cancer Ki67 expression prediction by DCE-MRI radiomics features.
Ma W; Ji Y; Qi L; Guo X; Jian X; Liu P
Clin Radiol; 2018 Oct; 73(10):909.e1-909.e5. PubMed ID: 29970244
[TBL] [Abstract][Full Text] [Related]
2. Invasive ductal breast cancer: preoperative predict Ki-67 index based on radiomics of ADC maps.
Zhang Y; Zhu Y; Zhang K; Liu Y; Cui J; Tao J; Wang Y; Wang S
Radiol Med; 2020 Feb; 125(2):109-116. PubMed ID: 31696388
[TBL] [Abstract][Full Text] [Related]
3. Breast Cancer Molecular Subtype Prediction by Mammographic Radiomic Features.
Ma W; Zhao Y; Ji Y; Guo X; Jian X; Liu P; Wu S
Acad Radiol; 2019 Feb; 26(2):196-201. PubMed ID: 29526548
[TBL] [Abstract][Full Text] [Related]
4. Invasive ductal breast cancer molecular subtype prediction by MRI radiomic and clinical features based on machine learning.
Sheng W; Xia S; Wang Y; Yan L; Ke S; Mellisa E; Gong F; Zheng Y; Tang T
Front Oncol; 2022; 12():964605. PubMed ID: 36172153
[TBL] [Abstract][Full Text] [Related]
5. Breast cancer Ki-67 expression prediction by digital breast tomosynthesis radiomics features.
Tagliafico AS; Bignotti B; Rossi F; Matos J; Calabrese M; Valdora F; Houssami N
Eur Radiol Exp; 2019 Aug; 3(1):36. PubMed ID: 31414273
[TBL] [Abstract][Full Text] [Related]
6. Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer.
Zheng Z; Gu Z; Xu F; Maskey N; He Y; Yan Y; Xu T; Liu S; Yao X
Cancer Imaging; 2021 Dec; 21(1):65. PubMed ID: 34863282
[TBL] [Abstract][Full Text] [Related]
7. An MRI-based Radiomics Classifier for Preoperative Prediction of Ki-67 Status in Breast Cancer.
Liang C; Cheng Z; Huang Y; He L; Chen X; Ma Z; Huang X; Liang C; Liu Z
Acad Radiol; 2018 Sep; 25(9):1111-1117. PubMed ID: 29428211
[TBL] [Abstract][Full Text] [Related]
8. Systematic radiomics analysis based on multiparameter MRI to preoperatively predict the expression of Ki67 and histological grade in patients with bladder cancer.
Fan X; Yu H; Ni X; Chen G; Li T; Chen J; He M; Liu H; Wang H; Yin X
Br J Radiol; 2023 Apr; 96(1145):20221086. PubMed ID: 36883677
[TBL] [Abstract][Full Text] [Related]
9. Prediction of prostate cancer aggressiveness with a combination of radiomics and machine learning-based analysis of dynamic contrast-enhanced MRI.
Liu B; Cheng J; Guo DJ; He XJ; Luo YD; Zeng Y; Li CM
Clin Radiol; 2019 Nov; 74(11):896.e1-896.e8. PubMed ID: 31495546
[TBL] [Abstract][Full Text] [Related]
10. Radiomics Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Sentinel Lymph Node Metastasis in Breast Cancer.
Liu J; Sun D; Chen L; Fang Z; Song W; Guo D; Ni T; Liu C; Feng L; Xia Y; Zhang X; Li C
Front Oncol; 2019; 9():980. PubMed ID: 31632912
[No Abstract] [Full Text] [Related]
11. Performance of radiomics models for tumour-infiltrating lymphocyte (TIL) prediction in breast cancer: the role of the dynamic contrast-enhanced (DCE) MRI phase.
Tang WJ; Kong QC; Cheng ZX; Liang YS; Jin Z; Chen LX; Hu WK; Liang YY; Wei XH; Guo Y; Jiang XQ
Eur Radiol; 2022 Feb; 32(2):864-875. PubMed ID: 34430998
[TBL] [Abstract][Full Text] [Related]
12. Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI.
Zhang Y; Zhu Y; Shi X; Tao J; Cui J; Dai Y; Zheng M; Wang S
Acad Radiol; 2019 Sep; 26(9):1262-1268. PubMed ID: 30377057
[TBL] [Abstract][Full Text] [Related]
13. Identifying Triple-Negative Breast Cancer Using Background Parenchymal Enhancement Heterogeneity on Dynamic Contrast-Enhanced MRI: A Pilot Radiomics Study.
Wang J; Kato F; Oyama-Manabe N; Li R; Cui Y; Tha KK; Yamashita H; Kudo K; Shirato H
PLoS One; 2015; 10(11):e0143308. PubMed ID: 26600392
[TBL] [Abstract][Full Text] [Related]
14. Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer.
Ma M; Gan L; Jiang Y; Qin N; Li C; Zhang Y; Wang X
Comput Math Methods Med; 2021; 2021():2140465. PubMed ID: 34422088
[TBL] [Abstract][Full Text] [Related]
15. Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer.
Liu M; Mao N; Ma H; Dong J; Zhang K; Che K; Duan S; Zhang X; Shi Y; Xie H
Cancer Imaging; 2020 Sep; 20(1):65. PubMed ID: 32933585
[TBL] [Abstract][Full Text] [Related]
16. Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.
Huang Y; Wei L; Hu Y; Shao N; Lin Y; He S; Shi H; Zhang X; Lin Y
Front Oncol; 2021; 11():706733. PubMed ID: 34490107
[TBL] [Abstract][Full Text] [Related]
17. DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 status of estrogen receptor-positive breast cancers.
Fan M; Cheng H; Zhang P; Gao X; Zhang J; Shao G; Li L
J Magn Reson Imaging; 2018 Jul; 48(1):237-247. PubMed ID: 29219225
[TBL] [Abstract][Full Text] [Related]
18. Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using radiomics of pretreatment dynamic contrast-enhanced MRI.
Yoshida K; Kawashima H; Kannon T; Tajima A; Ohno N; Terada K; Takamatsu A; Adachi H; Ohno M; Miyati T; Ishikawa S; Ikeda H; Gabata T
Magn Reson Imaging; 2022 Oct; 92():19-25. PubMed ID: 35636571
[TBL] [Abstract][Full Text] [Related]
19. Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data.
Ni J; Zhang H; Yang Q; Fan X; Xu J; Sun J; Zhang J; Hu Y; Xiao Z; Zhao Y; Zhu H; Shi X; Feng W; Wang J; Wan C; Zhang X; Liu Y; You Y; Yu Y
Acad Radiol; 2024 Mar; ():. PubMed ID: 38458887
[TBL] [Abstract][Full Text] [Related]
20. Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics.
Fan M; Yuan W; Zhao W; Xu M; Wang S; Gao X; Li L
IEEE J Biomed Health Inform; 2020 Jun; 24(6):1632-1642. PubMed ID: 31794406
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
