186 related articles for article (PubMed ID: 32923388)
1. Identification of Predominant Histopathological Growth Patterns of Colorectal Liver Metastasis by Multi-Habitat and Multi-Sequence Based Radiomics Analysis.
Han Y; Chai F; Wei J; Yue Y; Cheng J; Gu D; Zhang Y; Tong T; Sheng W; Hong N; Ye Y; Wang Y; Tian J
Front Oncol; 2020; 10():1363. PubMed ID: 32923388
[No Abstract] [Full Text] [Related]
2. Prediction of Histopathologic Growth Patterns of Colorectal Liver Metastases with a Noninvasive Imaging Method.
Cheng J; Wei J; Tong T; Sheng W; Zhang Y; Han Y; Gu D; Hong N; Ye Y; Tian J; Wang Y
Ann Surg Oncol; 2019 Dec; 26(13):4587-4598. PubMed ID: 31605342
[TBL] [Abstract][Full Text] [Related]
3. Prediction of transformation in the histopathological growth pattern of colorectal liver metastases after chemotherapy using CT-based radiomics.
Wei S; Gou X; Zhang Y; Cui J; Liu X; Hong N; Sheng W; Cheng J; Wang Y
Clin Exp Metastasis; 2024 Apr; 41(2):143-154. PubMed ID: 38416301
[TBL] [Abstract][Full Text] [Related]
4. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules.
Hu T; Wang S; Huang L; Wang J; Shi D; Li Y; Tong T; Peng W
Eur Radiol; 2019 Jan; 29(1):439-449. PubMed ID: 29948074
[TBL] [Abstract][Full Text] [Related]
5. Development and external validation of MRI-based RAS mutation status prediction model for liver metastases of colorectal cancer.
Han Z; Tong Y; Zhu X; Sun D; Jia N; Feng Y; Yan K; Wei Y; He J; Ju H
J Surg Oncol; 2024 Mar; 129(3):556-567. PubMed ID: 37974474
[TBL] [Abstract][Full Text] [Related]
6. Radiomics Nomogram for Prediction of Peritoneal Metastasis in Patients With Gastric Cancer.
Huang W; Zhou K; Jiang Y; Chen C; Yuan Q; Han Z; Xie J; Yu S; Sun Z; Hu Y; Yu J; Liu H; Xiao R; Xu Y; Zhou Z; Li G
Front Oncol; 2020; 10():1416. PubMed ID: 32974149
[No Abstract] [Full Text] [Related]
7. A Delta-radiomics model for preoperative evaluation of Neoadjuvant chemotherapy response in high-grade osteosarcoma.
Lin P; Yang PF; Chen S; Shao YY; Xu L; Wu Y; Teng W; Zhou XZ; Li BH; Luo C; Xu LM; Huang M; Niu TY; Ye ZM
Cancer Imaging; 2020 Jan; 20(1):7. PubMed ID: 31937372
[TBL] [Abstract][Full Text] [Related]
8. Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer.
Yu FH; Wang JX; Ye XH; Deng J; Hang J; Yang B
Eur J Radiol; 2019 Oct; 119():108658. PubMed ID: 31521878
[TBL] [Abstract][Full Text] [Related]
9. Deep learning-based radiomics predicts response to chemotherapy in colorectal liver metastases.
Wei J; Cheng J; Gu D; Chai F; Hong N; Wang Y; Tian J
Med Phys; 2021 Jan; 48(1):513-522. PubMed ID: 33119899
[TBL] [Abstract][Full Text] [Related]
10. Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients.
Chen S; Shu Z; Li Y; Chen B; Tang L; Mo W; Shao G; Shao F
Front Oncol; 2020; 10():1410. PubMed ID: 32923392
[No Abstract] [Full Text] [Related]
11. MR-Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph-Vascular Space Invasion preoperatively.
Li Z; Li H; Wang S; Dong D; Yin F; Chen A; Wang S; Zhao G; Fang M; Tian J; Wu S; Wang H
J Magn Reson Imaging; 2019 May; 49(5):1420-1426. PubMed ID: 30362652
[TBL] [Abstract][Full Text] [Related]
12. MRI radiomics analysis for predicting preoperative synchronous distant metastasis in patients with rectal cancer.
Liu H; Zhang C; Wang L; Luo R; Li J; Zheng H; Yin Q; Zhang Z; Duan S; Li X; Wang D
Eur Radiol; 2019 Aug; 29(8):4418-4426. PubMed ID: 30413955
[TBL] [Abstract][Full Text] [Related]
13. Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.
Huang YQ; Liang CH; He L; Tian J; Liang CS; Chen X; Ma ZL; Liu ZY
J Clin Oncol; 2016 Jun; 34(18):2157-64. PubMed ID: 27138577
[TBL] [Abstract][Full Text] [Related]
14. Radiomics Nomogram Building From Multiparametric MRI to Predict Grade in Patients With Glioma: A Cohort Study.
Wang Q; Li Q; Mi R; Ye H; Zhang H; Chen B; Li Y; Huang G; Xia J
J Magn Reson Imaging; 2019 Mar; 49(3):825-833. PubMed ID: 30260592
[TBL] [Abstract][Full Text] [Related]
15. Preoperative Prediction of Extramural Venous Invasion in Rectal Cancer: Comparison of the Diagnostic Efficacy of Radiomics Models and Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging.
Yu X; Song W; Guo D; Liu H; Zhang H; He X; Song J; Zhou J; Liu X
Front Oncol; 2020; 10():459. PubMed ID: 32328461
[No Abstract] [Full Text] [Related]
16. A Computed Tomography-Based Radiomics Nomogram to Preoperatively Predict Tumor Necrosis in Patients With Clear Cell Renal Cell Carcinoma.
Jiang Y; Li W; Huang C; Tian C; Chen Q; Zeng X; Cao Y; Chen Y; Yang Y; Liu H; Bo Y; Luo C; Li Y; Zhang T; Wang R
Front Oncol; 2020; 10():592. PubMed ID: 32547934
[No Abstract] [Full Text] [Related]
17. A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer.
Wu S; Zheng J; Li Y; Yu H; Shi S; Xie W; Liu H; Su Y; Huang J; Lin T
Clin Cancer Res; 2017 Nov; 23(22):6904-6911. PubMed ID: 28874414
[No Abstract] [Full Text] [Related]
18. Radiomics Analysis of Iodine-Based Material Decomposition Images With Dual-Energy Computed Tomography Imaging for Preoperatively Predicting Microsatellite Instability Status in Colorectal Cancer.
Wu J; Zhang Q; Zhao Y; Liu Y; Chen A; Li X; Wu T; Li J; Guo Y; Liu A
Front Oncol; 2019; 9():1250. PubMed ID: 31824843
[No Abstract] [Full Text] [Related]
19. Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach.
Zheng J; Kong J; Wu S; Li Y; Cai J; Yu H; Xie W; Qin H; Wu Z; Huang J; Lin T
Cancer; 2019 Dec; 125(24):4388-4398. PubMed ID: 31469418
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of Lymph Node Metastasis in Advanced Gastric Cancer Using Magnetic Resonance Imaging-Based Radiomics.
Chen W; Wang S; Dong D; Gao X; Zhou K; Li J; Lv B; Li H; Wu X; Fang M; Tian J; Xu M
Front Oncol; 2019; 9():1265. PubMed ID: 31824847
[No Abstract] [Full Text] [Related]
[Next] [New Search]
