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.
161 related articles for article (PubMed ID: 39191174)
21. A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial. Zhu T; Huang YH; Li W; Wu CG; Zhang YM; Zheng XX; Zhang TF; Lin YY; Liu ZY; Ye GL; Lin Y; Wu ZY; Wang K Br J Cancer; 2024 Sep; 131(4):692-701. PubMed ID: 38918556 [TBL] [Abstract][Full Text] [Related]
22. Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography. Wang Q; Lin Y; Ding C; Guan W; Zhang X; Jia J; Zhou W; Liu Z; Bai G Eur Radiol; 2024 Sep; 34(9):6121-6131. PubMed ID: 38337068 [TBL] [Abstract][Full Text] [Related]
23. Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor. Shi W; Su Y; Zhang R; Xia W; Lian Z; Mao N; Wang Y; Zhang A; Gao X; Zhang Y Cancer Imaging; 2024 Sep; 24(1):122. PubMed ID: 39272199 [TBL] [Abstract][Full Text] [Related]
24. A non-invasive preoperative prediction model for predicting axillary lymph node metastasis in breast cancer based on a machine learning approach: combining ultrasonographic parameters and breast gamma specific imaging features. Cai R; Deng L; Zhang H; Zhang H; Wu Q Radiat Oncol; 2024 May; 19(1):63. PubMed ID: 38802938 [TBL] [Abstract][Full Text] [Related]
25. Computed tomography reconstruction for evaluating response in axillary lymph nodes of breast cancer after neoadjuvant chemotherapy. Wang L; Li Y; Li J; Wang T; Xie Y; He Y; Fan Z; Ouyang T Clin Transl Oncol; 2021 Feb; 23(2):240-245. PubMed ID: 32519177 [TBL] [Abstract][Full Text] [Related]
26. MRI Volume Changes of Axillary Lymph Nodes as Predictor of Pathologic Complete Responses to Neoadjuvant Chemotherapy in Breast Cancer. Cattell RF; Kang JJ; Ren T; Huang PB; Muttreja A; Dacosta S; Li H; Baer L; Clouston S; Palermo R; Fisher P; Bernstein C; Cohen JA; Duong TQ Clin Breast Cancer; 2020 Feb; 20(1):68-79.e1. PubMed ID: 31327729 [TBL] [Abstract][Full Text] [Related]
27. Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer. Al-Hattali S; Vinnicombe SJ; Gowdh NM; Evans A; Armstrong S; Adamson D; Purdie CA; Macaskill EJ Cancer Imaging; 2019 Dec; 19(1):91. PubMed ID: 31878958 [TBL] [Abstract][Full Text] [Related]
28. Comparing shear wave elastography of breast tumors and axillary nodes in the axillary assessment after neoadjuvant chemotherapy in patients with node-positive breast cancer. Huang JX; Liu FT; Sun L; Ma C; Fu J; Wang XY; Huang GL; Zhang YT; Pei XQ Radiol Med; 2024 Aug; 129(8):1143-1155. PubMed ID: 39060887 [TBL] [Abstract][Full Text] [Related]
29. Development and validation of convolutional neural network-based model to predict the risk of sentinel or non-sentinel lymph node metastasis in patients with breast cancer: a machine learning study. Chen M; Kong C; Lin G; Chen W; Guo X; Chen Y; Cheng X; Chen M; Shi C; Xu M; Sun J; Lu C; Ji J EClinicalMedicine; 2023 Sep; 63():102176. PubMed ID: 37662514 [TBL] [Abstract][Full Text] [Related]
30. Development of an Ultrasound-based Nomogram for Predicting Pathologic Complete Response and Axillary Response in Node-Positive Patients with Triple- Negative Breast Cancer. Zhang M; Zha H; Pan J; Liu X; Zong M; Du L; Du Y Clin Breast Cancer; 2024 Aug; 24(6):e485-e494.e1. PubMed ID: 38627192 [TBL] [Abstract][Full Text] [Related]
31. Application of conventional ultrasonography combined with contrast-enhanced ultrasonography in the axillary lymph nodes and evaluation of the efficacy of neoadjuvant chemotherapy in breast cancer patients. Han X; Jin S; Yang H; Zhang J; Huang Z; Han J; He C; Guo H; Yang Y; Shan M; Zhang G Br J Radiol; 2021 Sep; 94(1125):20210520. PubMed ID: 34415197 [TBL] [Abstract][Full Text] [Related]
32. Is it always necessary to perform an axillary lymph node dissection after neoadjuvant chemotherapy for breast cancer? Osorio-Silla I; Gómez Valdazo A; Sánchez Méndez JI; York E; Díaz-Almirón M; Gómez Ramírez J; Rivas Fidalgo S; Oliver JM; Álvarez CM; Hardisson D; Díaz Miguel M; Lobo F; Díaz Domínguez J Ann R Coll Surg Engl; 2019 Mar; 101(3):186-192. PubMed ID: 30421628 [TBL] [Abstract][Full Text] [Related]
33. Deep learning radiomics of ultrasonography: Identifying the risk of axillary non-sentinel lymph node involvement in primary breast cancer. Guo X; Liu Z; Sun C; Zhang L; Wang Y; Li Z; Shi J; Wu T; Cui H; Zhang J; Tian J; Tian J EBioMedicine; 2020 Oct; 60():103018. PubMed ID: 32980697 [TBL] [Abstract][Full Text] [Related]
34. Combining conventional ultrasound and sonoelastography to predict axillary status after neoadjuvant chemotherapy for breast cancer. Huang JX; Lin SY; Ou Y; Shi CG; Zhong Y; Wei MJ; Pei XQ Eur Radiol; 2022 Sep; 32(9):5986-5996. PubMed ID: 35364714 [TBL] [Abstract][Full Text] [Related]
35. Peritumoral edema enhances MRI-based deep learning radiomic model for axillary lymph node metastasis burden prediction in breast cancer. Luo H; Chen Z; Xu H; Ren J; Zhou P Sci Rep; 2024 Aug; 14(1):18900. PubMed ID: 39143315 [TBL] [Abstract][Full Text] [Related]
36. 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]
37. 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]
38. Preoperative MRI improves prediction of extensive occult axillary lymph node metastases in breast cancer patients with a positive sentinel lymph node biopsy. Loiselle C; Eby PR; Kim JN; Calhoun KE; Allison KH; Gadi VK; Peacock S; Storer BE; Mankoff DA; Partridge SC; Lehman CD Acad Radiol; 2014 Jan; 21(1):92-8. PubMed ID: 24331270 [TBL] [Abstract][Full Text] [Related]
39. Deep learning-enabled fully automated pipeline system for segmentation and classification of single-mass breast lesions using contrast-enhanced mammography: a prospective, multicentre study. Zheng T; Lin F; Li X; Chu T; Gao J; Zhang S; Li Z; Gu Y; Wang S; Zhao F; Ma H; Xie H; Xu C; Zhang H; Mao N EClinicalMedicine; 2023 Apr; 58():101913. PubMed ID: 36969336 [TBL] [Abstract][Full Text] [Related]
40. Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method. Qu YH; Zhu HT; Cao K; Li XT; Ye M; Sun YS Thorac Cancer; 2020 Mar; 11(3):651-658. PubMed ID: 31944571 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]