171 related articles for article (PubMed ID: 38787429)
21. T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer.
Li H; Chai L; Pu H; Yin LL; Li M; Zhang X; Liu YS; Pang MH; Lu T
Insights Imaging; 2024 Feb; 15(1):57. PubMed ID: 38411722
[TBL] [Abstract][Full Text] [Related]
22. Application of radiomics feature captured from MRI for prediction of recurrence for glioma patients.
Liu C; Li Y; Xia X; Wang J; Hu C
J Cancer; 2022; 13(3):965-974. PubMed ID: 35154462
[No Abstract] [Full Text] [Related]
23. [Risk factor analysis on anastomotic leakage after laparoscopic surgery in rectal cancer patient with neoadjuvant therapy and establishment of a nomogram prediction model].
Jiang W; Feng MY; Dong XY; Dong SM; Zheng JX; Liu XM; Liu WJ; Yan J
Zhonghua Wei Chang Wai Ke Za Zhi; 2019 Aug; 22(8):748-754. PubMed ID: 31422613
[No Abstract] [Full Text] [Related]
24. A predictive nomogram for individualized recurrence stratification of bladder cancer using multiparametric MRI and clinical risk factors.
Xu X; Wang H; Du P; Zhang F; Li S; Zhang Z; Yuan J; Liang Z; Zhang X; Guo Y; Liu Y; Lu H
J Magn Reson Imaging; 2019 Dec; 50(6):1893-1904. PubMed ID: 30980695
[TBL] [Abstract][Full Text] [Related]
25. Long-term survival outcomes in invasive lobular carcinoma patients with and without preoperative MR imaging: a matched cohort study.
Ha SM; Chae EY; Cha JH; Kim HH; Shin HJ; Choi WJ
Eur Radiol; 2019 May; 29(5):2526-2534. PubMed ID: 30617471
[TBL] [Abstract][Full Text] [Related]
26. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
[TBL] [Abstract][Full Text] [Related]
27. Ultrasound-Based Radiomics Analysis for Predicting Disease-Free Survival of Invasive Breast Cancer.
Xiong L; Chen H; Tang X; Chen B; Jiang X; Liu L; Feng Y; Liu L; Li L
Front Oncol; 2021; 11():621993. PubMed ID: 33996546
[TBL] [Abstract][Full Text] [Related]
28. Texture analysis using machine learning-based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy.
Eun NL; Kang D; Son EJ; Youk JH; Kim JA; Gweon HM
Eur Radiol; 2021 Sep; 31(9):6916-6928. PubMed ID: 33693994
[TBL] [Abstract][Full Text] [Related]
29. HER2-Positive Breast Cancer: Association of MRI and Clinicopathologic Features With Tumor-Infiltrating Lymphocytes.
Lee HJ; Lee JE; Jeong WG; Ki SY; Park MH; Lee JS; Nah YK; Lim HS
AJR Am J Roentgenol; 2022 Feb; 218(2):258-269. PubMed ID: 34431365
[No Abstract] [Full Text] [Related]
30. A clinicopathological-imaging nomogram for the prediction of pathological complete response in breast cancer cases administered neoadjuvant therapy.
Yang W; Yang Y; Zhang C; Yin Q; Zhang N
Magn Reson Imaging; 2024 Sep; 111():120-130. PubMed ID: 38703971
[TBL] [Abstract][Full Text] [Related]
31. Development of a Prognostic App (iCanPredict) to Predict Survival for Chinese Women With Breast Cancer: Retrospective Study.
Ma Z; Huang S; Wu X; Huang Y; Chan SW; Lin Y; Zheng X; Zhu J
J Med Internet Res; 2022 Mar; 24(3):e35768. PubMed ID: 35262503
[TBL] [Abstract][Full Text] [Related]
32. Clinical Significance of Preoperative CT and MR Imaging Findings in the Prediction of Postoperative Recurrence of Spinal Giant Cell Tumor of Bone.
Wang QZ; Zhang EL; Xing XY; Su MY; Lang N
Orthop Surg; 2021 Dec; 13(8):2405-2416. PubMed ID: 34841660
[TBL] [Abstract][Full Text] [Related]
33. Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics.
Sheng DL; Shen XG; Shi ZT; Chang C; Li JW
Eur Radiol; 2022 Oct; 32(10):6575-6587. PubMed ID: 35759017
[TBL] [Abstract][Full Text] [Related]
34. Radiomics features based on automatic segmented MRI images: Prognostic biomarkers for triple-negative breast cancer treated with neoadjuvant chemotherapy.
Ma M; Gan L; Liu Y; Jiang Y; Xin L; Liu Y; Qin N; Cheng Y; Liu Q; Xu L; Zhang Y; Wang X; Zhang X; Ye J; Wang X
Eur J Radiol; 2022 Jan; 146():110095. PubMed ID: 34890936
[TBL] [Abstract][Full Text] [Related]
35. Prognostic Factors of Disease Recurrence in Breast Cancer Using Quantitative and Qualitative Magnetic Resonance Imaging (MRI) Parameters.
Lee J; Kim SH; Kang BJ
Sci Rep; 2020 May; 10(1):7598. PubMed ID: 32371907
[TBL] [Abstract][Full Text] [Related]
36. Intratumoral and peritumoral radiomics based on dynamic contrast-enhanced MRI for preoperative prediction of intraductal component in invasive breast cancer.
Xu H; Liu J; Chen Z; Wang C; Liu Y; Wang M; Zhou P; Luo H; Ren J
Eur Radiol; 2022 Jul; 32(7):4845-4856. PubMed ID: 35079887
[TBL] [Abstract][Full Text] [Related]
37. MR imaging features associated with distant metastasis-free survival of patients with invasive breast cancer: a case-control study.
Song SE; Shin SU; Moon HG; Ryu HS; Kim K; Moon WK
Breast Cancer Res Treat; 2017 Apr; 162(3):559-569. PubMed ID: 28185146
[TBL] [Abstract][Full Text] [Related]
38. Background parenchymal signal enhancement ratio at preoperative MR imaging: association with subsequent local recurrence in patients with ductal carcinoma in situ after breast conservation surgery.
Kim SA; Cho N; Ryu EB; Seo M; Bae MS; Chang JM; Moon WK
Radiology; 2014 Mar; 270(3):699-707. PubMed ID: 24126372
[TBL] [Abstract][Full Text] [Related]
39. Association of preoperative breast MRI features with locoregional recurrence after breast conservation therapy.
Bae MS; Chang JM; Cho N; Han W; Ryu HS; Moon WK
Acta Radiol; 2018 Apr; 59(4):409-417. PubMed ID: 28747131
[TBL] [Abstract][Full Text] [Related]
40.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]
