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.
250 related articles for article (PubMed ID: 33421823)
1. Axillary lymph node metastasis status prediction of early-stage breast cancer using convolutional neural networks. Lee YW; Huang CS; Shih CC; Chang RF Comput Biol Med; 2021 Mar; 130():104206. PubMed ID: 33421823 [TBL] [Abstract][Full Text] [Related]
2. Computer-aided prediction model for axillary lymph node metastasis in breast cancer using tumor morphological and textural features on ultrasound. Moon WK; Chen IL; Yi A; Bae MS; Shin SU; Chang RF Comput Methods Programs Biomed; 2018 Aug; 162():129-137. PubMed ID: 29903479 [TBL] [Abstract][Full Text] [Related]
3. Computer-aided prediction of axillary lymph node status in breast cancer using tumor surrounding tissue features in ultrasound images. Moon WK; Lee YW; Huang YS; Lee SH; Bae MS; Yi A; Huang CS; Chang RF Comput Methods Programs Biomed; 2017 Jul; 146():143-150. PubMed ID: 28688484 [TBL] [Abstract][Full Text] [Related]
4. Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning. Zhou LQ; Wu XL; Huang SY; Wu GG; Ye HR; Wei Q; Bao LY; Deng YB; Li XR; Cui XW; Dietrich CF Radiology; 2020 Jan; 294(1):19-28. PubMed ID: 31746687 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. Deep Learning Prediction of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Clinical Implication-Applied Preprocessed CT Images. Park TY; Kwon LM; Hyeon J; Cho BJ; Kim BJ Curr Oncol; 2024 Apr; 31(4):2278-2288. PubMed ID: 38668072 [No Abstract] [Full Text] [Related]
7. Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer. Wang X; Nie L; Zhu Q; Zuo Z; Liu G; Sun Q; Zhai J; Li J BMC Cancer; 2024 Jul; 24(1):910. PubMed ID: 39075447 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. Efficient Axillary Lymph Node Detection Via Two-stage Spatial-information-fusion-based CNN. Liu Z; Huang D; Yang C; Shu J; Li J; Qin N Comput Methods Programs Biomed; 2022 Aug; 223():106953. PubMed ID: 35772232 [TBL] [Abstract][Full Text] [Related]
11. Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning. Liu Z; Ni S; Yang C; Sun W; Huang D; Su H; Shu J; Qin N Comput Biol Med; 2021 Sep; 136():104715. PubMed ID: 34388460 [TBL] [Abstract][Full Text] [Related]
12. Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region. Sun Q; Lin X; Zhao Y; Li L; Yan K; Liang D; Sun D; Li ZC Front Oncol; 2020; 10():53. PubMed ID: 32083007 [No Abstract] [Full Text] [Related]
13. Prediction of axillary lymph node metastasis in early breast cancer patients with ultrasonic videos based deep learning. Li WB; Du ZC; Liu YJ; Gao JX; Wang JG; Dai Q; Huang WH Front Oncol; 2023; 13():1219838. PubMed ID: 37719009 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Usefulness of preoperative breast magnetic resonance imaging with a dedicated axillary sequence for the detection of axillary lymph node metastasis in patients with early ductal breast cancer. Ahn HS; Jang M; Kim SM; La Yun B; Lee SH Radiol Med; 2019 Dec; 124(12):1220-1228. PubMed ID: 31422573 [TBL] [Abstract][Full Text] [Related]
16. Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study. Zhou H; Hua Z; Gao J; Lin F; Chen Y; Zhang S; Zheng T; Wang Z; Shao H; Li W; Liu F; Li Q; Chen J; Wang X; Zhao F; Qu N; Xie H; Ma H; Zhang H; Mao N J Magn Reson Imaging; 2024 May; 59(5):1710-1722. PubMed ID: 37497811 [TBL] [Abstract][Full Text] [Related]
17. 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]
18. Could Ultrasound-Based Radiomics Noninvasively Predict Axillary Lymph Node Metastasis in Breast Cancer? Qiu X; Jiang Y; Zhao Q; Yan C; Huang M; Jiang T J Ultrasound Med; 2020 Oct; 39(10):1897-1905. PubMed ID: 32329142 [TBL] [Abstract][Full Text] [Related]
19. Magnetic resonance imaging features for predicting axillary lymph node metastasis in patients with breast cancer. Zhao M; Wu Q; Guo L; Zhou L; Fu K Eur J Radiol; 2020 Aug; 129():109093. PubMed ID: 32512504 [TBL] [Abstract][Full Text] [Related]
20. Nomogram based on radiomics analysis of primary breast cancer ultrasound images: prediction of axillary lymph node tumor burden in patients. Gao Y; Luo Y; Zhao C; Xiao M; Ma L; Li W; Qin J; Zhu Q; Jiang Y Eur Radiol; 2021 Feb; 31(2):928-937. PubMed ID: 32845388 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]