208 related articles for article (PubMed ID: 38627678)
1. Lymph node metastasis prediction and biological pathway associations underlying DCE-MRI deep learning radiomics in invasive breast cancer.
Liu W; Chen W; Xia J; Lu Z; Fu Y; Li Y; Tan Z
BMC Med Imaging; 2024 Apr; 24(1):91. PubMed ID: 38627678
[TBL] [Abstract][Full Text] [Related]
2. Deep learning radiomics of ultrasonography for comprehensively predicting tumor and axillary lymph node status after neoadjuvant chemotherapy in breast cancer patients: A multicenter study.
Gu J; Tong T; Xu D; Cheng F; Fang C; He C; Wang J; Wang B; Yang X; Wang K; Tian J; Jiang T
Cancer; 2023 Feb; 129(3):356-366. PubMed ID: 36401611
[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. 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]
5. Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.
Li X; Yang L; Jiao X
Acad Radiol; 2023 Jul; 30(7):1281-1287. PubMed ID: 36376154
[TBL] [Abstract][Full Text] [Related]
6. Constructing a Deep Learning Radiomics Model Based on X-ray Images and Clinical Data for Predicting and Distinguishing Acute and Chronic Osteoporotic Vertebral Fractures: A Multicenter Study.
Zhang J; Xia L; Tang J; Xia J; Liu Y; Zhang W; Liu J; Liang Z; Zhang X; Zhang L; Tang G
Acad Radiol; 2024 May; 31(5):2011-2026. PubMed ID: 38016821
[TBL] [Abstract][Full Text] [Related]
7. Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.
Gao J; Zhong X; Li W; Li Q; Shao H; Wang Z; Dai Y; Ma H; Shi Y; Zhang H; Duan S; Zhang K; Yang P; Zhao F; Zhang H; Xie H; Mao N
J Magn Reson Imaging; 2023 Jun; 57(6):1842-1853. PubMed ID: 36219519
[TBL] [Abstract][Full Text] [Related]
8. Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI.
Yang X; Fan X; Lin S; Zhou Y; Liu H; Wang X; Zuo Z; Zeng Y
J Magn Reson Imaging; 2024 Jun; 59(6):2238-2249. PubMed ID: 37855421
[TBL] [Abstract][Full Text] [Related]
9. Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics.
Chen W; Lin G; Kong C; Wu X; Hu Y; Chen M; Xia S; Lu C; Xu M; Ji J
Br J Radiol; 2024 Feb; 97(1154):439-450. PubMed ID: 38308028
[TBL] [Abstract][Full Text] [Related]
10. Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.
Chen Y; Wang L; Dong X; Luo R; Ge Y; Liu H; Zhang Y; Wang D
J Digit Imaging; 2023 Aug; 36(4):1323-1331. PubMed ID: 36973631
[TBL] [Abstract][Full Text] [Related]
11. Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.
Zhang B; Yu Y; Mao Y; Wang H; Lv M; Su X; Wang Y; Li Z; Zhang Z; Bian T; Wang Q
Acad Radiol; 2024 Mar; 31(3):800-811. PubMed ID: 37914627
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE-MRI Radiomics Nomogram.
Liu Y; Li X; Zhu L; Zhao Z; Wang T; Zhang X; Cai B; Li L; Ma M; Ma X; Ming J
Contrast Media Mol Imaging; 2022; 2022():6729473. PubMed ID: 36051932
[TBL] [Abstract][Full Text] [Related]
14. Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer.
Liu M; Mao N; Ma H; Dong J; Zhang K; Che K; Duan S; Zhang X; Shi Y; Xie H
Cancer Imaging; 2020 Sep; 20(1):65. PubMed ID: 32933585
[TBL] [Abstract][Full Text] [Related]
15. Deep Learning Radiomics Nomogram Based on Multiphase Computed Tomography for Predicting Axillary Lymph Node Metastasis in Breast Cancer.
Zhang J; Yin W; Yang L; Yao X
Mol Imaging Biol; 2024 Feb; 26(1):90-100. PubMed ID: 37563517
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Axillary Lymph Node Metastatic Load of Breast Cancer Based on Ultrasound Deep Learning Radiomics Nomogram.
Zhang H; Zhao T; Zhang S; Sun J; Zhang F; Li X; Ni X
Technol Cancer Res Treat; 2023; 22():15330338231166218. PubMed ID: 36987661
[No Abstract] [Full Text] [Related]
17. Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer.
Li J; Dong D; Fang M; Wang R; Tian J; Li H; Gao J
Eur Radiol; 2020 Apr; 30(4):2324-2333. PubMed ID: 31953668
[TBL] [Abstract][Full Text] [Related]
18. One 3D VOI-based deep learning radiomics strategy, clinical model and radiologists for predicting lymph node metastases in pancreatic ductal adenocarcinoma based on multiphasic contrast-enhanced computer tomography.
Liao H; Yang J; Li Y; Liang H; Ye J; Liu Y
Front Oncol; 2022; 12():990156. PubMed ID: 36158647
[TBL] [Abstract][Full Text] [Related]
19. Predictive nomogram for lymph node metastasis and survival in gastric cancer using contrast-enhanced computed tomography-based radiomics: a retrospective study.
Zhang W; Wang S; Dong Q; Chen W; Wang P; Zhu G; Chen X; Cai Y
PeerJ; 2024; 12():e17111. PubMed ID: 38525272
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
