115 related articles for article (PubMed ID: 38607282)
21. Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.
Joo MW; Ko T; Kim MS; Lee YS; Shin SH; Chung YG; Lee HK
Clin Orthop Relat Res; 2023 Nov; 481(11):2247-2256. PubMed ID: 37615504
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images.
Zhou J; Luo LY; Dou Q; Chen H; Chen C; Li GJ; Jiang ZF; Heng PA
J Magn Reson Imaging; 2019 Oct; 50(4):1144-1151. PubMed ID: 30924997
[TBL] [Abstract][Full Text] [Related]
24. Machine Learning-Based Breast Tumor Ultrasound Radiomics for Pre-operative Prediction of Axillary Sentinel Lymph Node Metastasis Burden in Early-Stage Invasive Breast Cancer.
Yao J; Zhou W; Xu S; Jia X; Zhou J; Chen X; Zhan W
Ultrasound Med Biol; 2024 Feb; 50(2):229-236. PubMed ID: 37951821
[TBL] [Abstract][Full Text] [Related]
25. Artificial neural network models to predict nodal status in clinically node-negative breast cancer.
Dihge L; Ohlsson M; Edén P; Bendahl PO; Rydén L
BMC Cancer; 2019 Jun; 19(1):610. PubMed ID: 31226956
[TBL] [Abstract][Full Text] [Related]
26. Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer using tumor heterogeneity and angiogenesis properties on MRI.
Lee JY; Lee KS; Seo BK; Cho KR; Woo OH; Song SE; Kim EK; Lee HY; Kim JS; Cha J
Eur Radiol; 2022 Jan; 32(1):650-660. PubMed ID: 34226990
[TBL] [Abstract][Full Text] [Related]
27. Predicting Axillary Response to Neoadjuvant Chemotherapy: Breast MRI and US in Patients with Node-Positive Breast Cancer.
Kim R; Chang JM; Lee HB; Lee SH; Kim SY; Kim ES; Cho N; Moon WK
Radiology; 2019 Oct; 293(1):49-57. PubMed ID: 31407967
[TBL] [Abstract][Full Text] [Related]
28. Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
Chai R; Ma H; Xu M; Arefan D; Cui X; Liu Y; Zhang L; Wu S; Xu K
J Magn Reson Imaging; 2019 Oct; 50(4):1125-1132. PubMed ID: 30848041
[TBL] [Abstract][Full Text] [Related]
29. Machine learning prediction of axillary lymph node metastasis in breast cancer: 2D versus 3D radiomic features.
Arefan D; Chai R; Sun M; Zuley ML; Wu S
Med Phys; 2020 Dec; 47(12):6334-6342. PubMed ID: 33058224
[TBL] [Abstract][Full Text] [Related]
30. 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]
31. Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Intra-peritumoral Textural Transition Analysis based on Dynamic Contrast-enhanced Magnetic Resonance Imaging.
Zhan C; Hu Y; Wang X; Liu H; Xia L; Ai T
Acad Radiol; 2022 Jan; 29 Suppl 1():S107-S115. PubMed ID: 33712393
[TBL] [Abstract][Full Text] [Related]
32. Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using CNN Based on Multiparametric MRI.
Wang Z; Sun H; Li J; Chen J; Meng F; Li H; Han L; Zhou S; Yu T
J Magn Reson Imaging; 2022 Sep; 56(3):700-709. PubMed ID: 35108415
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. Machine learning-based MRI texture analysis to predict occult lymph node metastasis in early-stage oral tongue squamous cell carcinoma.
Yuan Y; Ren J; Tao X
Eur Radiol; 2021 Sep; 31(9):6429-6437. PubMed ID: 33569617
[TBL] [Abstract][Full Text] [Related]
35. Prediction of breast cancer molecular subtypes using DCE-MRI based on CNNs combined with ensemble learning.
Sun R; Meng Z; Hou X; Chen Y; Yang Y; Huang G; Nie S
Phys Med Biol; 2021 Aug; 66(17):. PubMed ID: 34330117
[TBL] [Abstract][Full Text] [Related]
36. Intratumoral and Peritumoral Analysis of Mammography, Tomosynthesis, and Multiparametric MRI for Predicting Ki-67 Level in Breast Cancer: a Radiomics-Based Study.
Jiang T; Song J; Wang X; Niu S; Zhao N; Dong Y; Wang X; Luo Y; Jiang X
Mol Imaging Biol; 2022 Aug; 24(4):550-559. PubMed ID: 34904187
[TBL] [Abstract][Full Text] [Related]
37. Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.
Ozaki J; Fujioka T; Yamaga E; Hayashi A; Kujiraoka Y; Imokawa T; Takahashi K; Okawa S; Yashima Y; Mori M; Kubota K; Oda G; Nakagawa T; Tateishi U
Jpn J Radiol; 2022 Aug; 40(8):814-822. PubMed ID: 35284996
[TBL] [Abstract][Full Text] [Related]
38. Weakly supervised breast lesion detection in DCE-MRI using self-transfer learning.
Sun R; Zhang X; Xie Y; Nie S
Med Phys; 2023 Aug; 50(8):4960-4972. PubMed ID: 36820793
[TBL] [Abstract][Full Text] [Related]
39. 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]
40. Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.
Tang Y; Yang CM; Su S; Wang WJ; Fan LP; Shu J
BMC Cancer; 2021 Nov; 21(1):1268. PubMed ID: 34819043
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
