These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
131 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. A comprehensive approach for evaluating lymphovascular invasion in invasive breast cancer: Leveraging multimodal MRI findings, radiomics, and deep learning analysis of intra- and peritumoral regions. Liu W; Li L; Deng J; Li W Comput Med Imaging Graph; 2024 Sep; 116():102415. PubMed ID: 39032451 [TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. 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]
7. 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]
8. 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]
9. 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]
10. 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]
11. 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]
12. 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]
13. 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]
14. 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]
15. 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]
16. 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]
17. 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]
18. 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]
19. 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]
20. 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] [Next] [New Search]