142 related articles for article (PubMed ID: 37648970)
1. Automated breast volume scanner based Radiomics for non-invasively prediction of lymphovascular invasion status in breast cancer.
Li Y; Wu X; Yan Y; Zhou P
BMC Cancer; 2023 Aug; 23(1):813. PubMed ID: 37648970
[TBL] [Abstract][Full Text] [Related]
2. Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.
Liu Z; Feng B; Li C; Chen Y; Chen Q; Li X; Guan J; Chen X; Cui E; Li R; Li Z; Long W
J Magn Reson Imaging; 2019 Sep; 50(3):847-857. PubMed ID: 30773770
[TBL] [Abstract][Full Text] [Related]
3. Prediction of Lymphovascular invasion status in breast cancer based on magnetic resonance imaging radiomics features.
Li X; Luo K; Zhang N; Chen W; Li B; Lu Z; Chen Y; Wu K
Magn Reson Imaging; 2024 Jun; 109():91-95. PubMed ID: 38467265
[TBL] [Abstract][Full Text] [Related]
4. Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma.
Zhang J; Wang G; Ren J; Yang Z; Li D; Cui Y; Yang X
Eur Radiol; 2022 Jun; 32(6):4079-4089. PubMed ID: 35050415
[TBL] [Abstract][Full Text] [Related]
5. MRI Radiomics of Breast Cancer: Machine Learning-Based Prediction of Lymphovascular Invasion Status.
Kayadibi Y; Kocak B; Ucar N; Akan YN; Yildirim E; Bektas S
Acad Radiol; 2022 Jan; 29 Suppl 1():S126-S134. PubMed ID: 34876340
[TBL] [Abstract][Full Text] [Related]
6. Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.
Zheng H; Jian L; Li L; Liu W; Chen W
Cancer Med; 2024 Feb; 13(3):e6932. PubMed ID: 38230837
[TBL] [Abstract][Full Text] [Related]
7. Machine learning analysis for the noninvasive prediction of lymphovascular invasion in gastric cancer using PET/CT and enhanced CT-based radiomics and clinical variables.
Fan L; Li J; Zhang H; Yin H; Zhang R; Zhang J; Chen X
Abdom Radiol (NY); 2022 Apr; 47(4):1209-1222. PubMed ID: 35089370
[TBL] [Abstract][Full Text] [Related]
8. Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound.
Xu ML; Zeng SE; Li F; Cui XW; Liu GF
Front Oncol; 2022; 12():1071677. PubMed ID: 36568215
[TBL] [Abstract][Full Text] [Related]
9. Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer.
Tong P; Sun D; Chen G; Ni J; Li Y
BMC Cancer; 2023 Jan; 23(1):61. PubMed ID: 36650498
[TBL] [Abstract][Full Text] [Related]
10. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
[TBL] [Abstract][Full Text] [Related]
11. Intratumoral and peritumoral radiomics nomograms for the preoperative prediction of lymphovascular invasion and overall survival in non-small cell lung cancer.
Chen Q; Shao J; Xue T; Peng H; Li M; Duan S; Feng F
Eur Radiol; 2023 Feb; 33(2):947-958. PubMed ID: 36064979
[TBL] [Abstract][Full Text] [Related]
12. MRI-Based Radiomics for Preoperative Prediction of Lymphovascular Invasion in Patients With Invasive Breast Cancer.
Nijiati M; Aihaiti D; Huojia A; Abulizi A; Mutailifu S; Rouzi N; Dai G; Maimaiti P
Front Oncol; 2022; 12():876624. PubMed ID: 35734595
[TBL] [Abstract][Full Text] [Related]
13. Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma.
Li Y; Yu M; Wang G; Yang L; Ma C; Wang M; Yue M; Cong M; Ren J; Shi G
Front Oncol; 2021; 11():644165. PubMed ID: 34055613
[TBL] [Abstract][Full Text] [Related]
14. Radiomics Analysis on Digital Breast Tomosynthesis: Preoperative Evaluation of Lymphovascular Invasion Status in Invasive Breast Cancer.
Wang D; Liu M; Zhuang Z; Wu S; Zhou P; Chen X; Zhu H; Liu H; Zhang L
Acad Radiol; 2022 Dec; 29(12):1773-1782. PubMed ID: 35400556
[TBL] [Abstract][Full Text] [Related]
15. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
16. Intra- and peritumoral radiomics features based on multicenter automatic breast volume scanner for noninvasive and preoperative prediction of HER2 status in breast cancer: a model ensemble research.
Wang H; Chen W; Jiang S; Li T; Chen F; Lei J; Li R; Xi L; Guo S
Sci Rep; 2024 Feb; 14(1):5020. PubMed ID: 38424285
[TBL] [Abstract][Full Text] [Related]
17. An Optimized Radiomics Model Based on Automated Breast Volume Scan Images to Identify Breast Lesions: Comparison of Machine Learning Methods: Comparison of Machine Learning Methods.
Wang H; Yang X; Ma S; Zhu K; Guo S
J Ultrasound Med; 2022 Jul; 41(7):1643-1655. PubMed ID: 34609750
[TBL] [Abstract][Full Text] [Related]
18. A radiomics nomogram based on contrast-enhanced CT for preoperative prediction of Lymphovascular invasion in esophageal squamous cell carcinoma.
Wang Y; Bai G; Huang W; Zhang H; Chen W
Front Oncol; 2023; 13():1208756. PubMed ID: 37465108
[TBL] [Abstract][Full Text] [Related]
19. MRI radiomics for the preoperative evaluation of lymphovascular invasion in breast cancer: A meta-analysis.
Ma Q; Li Z; Li W; Chen Q; Liu X; Feng W; Lei J
Eur J Radiol; 2023 Nov; 168():111127. PubMed ID: 37801997
[TBL] [Abstract][Full Text] [Related]
20. Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma.
Nie P; Yang G; Wang N; Yan L; Miao W; Duan Y; Wang Y; Gong A; Zhao Y; Wu J; Zhang C; Wang M; Cui J; Yu M; Li D; Sun Y; Wang Y; Wang Z
Eur J Nucl Med Mol Imaging; 2021 Jan; 48(1):217-230. PubMed ID: 32451603
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
