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.
425 related articles for article (PubMed ID: 34016188)
1. "Real-world" radiomics from multi-vendor MRI: an original retrospective study on the prediction of nodal status and disease survival in breast cancer, as an exemplar to promote discussion of the wider issues. Doran SJ; Kumar S; Orton M; d'Arcy J; Kwaks F; O'Flynn E; Ahmed Z; Downey K; Dowsett M; Turner N; Messiou C; Koh DM Cancer Imaging; 2021 May; 21(1):37. PubMed ID: 34016188 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients. Tahmassebi A; Wengert GJ; Helbich TH; Bago-Horvath Z; Alaei S; Bartsch R; Dubsky P; Baltzer P; Clauser P; Kapetas P; Morris EA; Meyer-Baese A; Pinker K Invest Radiol; 2019 Feb; 54(2):110-117. PubMed ID: 30358693 [TBL] [Abstract][Full Text] [Related]
5. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Braman NM; Etesami M; Prasanna P; Dubchuk C; Gilmore H; Tiwari P; Plecha D; Madabhushi A Breast Cancer Res; 2017 May; 19(1):57. PubMed ID: 28521821 [TBL] [Abstract][Full Text] [Related]
6. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer. Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800 [TBL] [Abstract][Full Text] [Related]
7. Radiomic nomogram based on MRI to predict grade of branching type intraductal papillary mucinous neoplasms of the pancreas: a multicenter study. Cui S; Tang T; Su Q; Wang Y; Shu Z; Yang W; Gong X Cancer Imaging; 2021 Mar; 21(1):26. PubMed ID: 33750453 [TBL] [Abstract][Full Text] [Related]
8. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI. Liu C; Ding J; Spuhler K; Gao Y; Serrano Sosa M; Moriarty M; Hussain S; He X; Liang C; Huang C J Magn Reson Imaging; 2019 Jan; 49(1):131-140. PubMed ID: 30171822 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study. Liu Z; Li Z; Qu J; Zhang R; Zhou X; Li L; Sun K; Tang Z; Jiang H; Li H; Xiong Q; Ding Y; Zhao X; Wang K; Liu Z; Tian J Clin Cancer Res; 2019 Jun; 25(12):3538-3547. PubMed ID: 30842125 [TBL] [Abstract][Full Text] [Related]
11. Machine learning on MRI radiomic features: identification of molecular subtype alteration in breast cancer after neoadjuvant therapy. Liu HQ; Lin SY; Song YD; Mai SY; Yang YD; Chen K; Wu Z; Zhao HY Eur Radiol; 2023 Apr; 33(4):2965-2974. PubMed ID: 36418622 [TBL] [Abstract][Full Text] [Related]
12. Development and Validation of MRI Radiomics Models to Differentiate HER2-Zero, -Low, and -Positive Breast Cancer. Peng Y; Zhang X; Qiu Y; Li B; Yang Z; Huang J; Lin J; Zheng C; Hu L; Shen J AJR Am J Roentgenol; 2024 Apr; 222(4):e2330603. PubMed ID: 38265001 [No Abstract] [Full Text] [Related]
13. Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes. Arefan D; Hausler RM; Sumkin JH; Sun M; Wu S BMC Cancer; 2021 Apr; 21(1):370. PubMed ID: 33827490 [TBL] [Abstract][Full Text] [Related]
14. Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer. Zhou X; Yi Y; Liu Z; Cao W; Lai B; Sun K; Li L; Zhou Z; Feng Y; Tian J Ann Surg Oncol; 2019 Jun; 26(6):1676-1684. PubMed ID: 30887373 [TBL] [Abstract][Full Text] [Related]
15. Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review. Granzier RWY; van Nijnatten TJA; Woodruff HC; Smidt ML; Lobbes MBI Eur J Radiol; 2019 Dec; 121():108736. PubMed ID: 31734639 [TBL] [Abstract][Full Text] [Related]
16. Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer. Bian T; Wu Z; Lin Q; Wang H; Ge Y; Duan S; Fu G; Cui C; Su X Br J Radiol; 2020 Nov; 93(1115):20200287. PubMed ID: 32822542 [TBL] [Abstract][Full Text] [Related]
17. Combining Dynamic Contrast-Enhanced Magnetic Resonance Imaging and Apparent Diffusion Coefficient Maps for a Radiomics Nomogram to Predict Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients. Chen X; Chen X; Yang J; Li Y; Fan W; Yang Z J Comput Assist Tomogr; 2020; 44(2):275-283. PubMed ID: 32004189 [TBL] [Abstract][Full Text] [Related]
18. Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Cui Y; Yang X; Shi Z; Yang Z; Du X; Zhao Z; Cheng X Eur Radiol; 2019 Mar; 29(3):1211-1220. PubMed ID: 30128616 [TBL] [Abstract][Full Text] [Related]
19. A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication. Wei J; Yang G; Hao X; Gu D; Tan Y; Wang X; Dong D; Zhang S; Wang L; Zhang H; Tian J Eur Radiol; 2019 Feb; 29(2):877-888. PubMed ID: 30039219 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]