Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis

Journal of Ultrasound in MedicineEarly View Letter to the Editor Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis Zhe Hu MM, Zhe Hu MM Jining Medical University, Jining, ChinaSearch for more papers by this authorZhikang Tian MM, Zhikang Tian MM Jining Medical University, Jining, ChinaSearch for more papers by this authorXi Wei MM, Xi Wei MM Jining Medical University, Jining, ChinaSearch for more papers by this authorYueqin Chen MD, Corresponding Author Yueqin Chen MD [email protected] orcid.org/0000-0003-0858-5720 Affiliated Hospital Of Jining Medical University, Jining, China Address correspondence to Yueqin Chen, Medical Imaging Department, Affiliated Hospital of Jining Medical University, 89 Guhuai Rd, Jining, 272007, China. E-mail: [email protected]Search for more papers by this author Zhe Hu MM, Zhe Hu MM Jining Medical University, Jining, ChinaSearch for more papers by this authorZhikang Tian MM, Zhikang Tian MM Jining Medical University, Jining, ChinaSearch for more papers by this authorXi Wei MM, Xi Wei MM Jining Medical University, Jining, ChinaSearch for more papers by this authorYueqin Chen MD, Corresponding Author Yueqin Chen MD [email protected] orcid.org/0000-0003-0858-5720 Affiliated Hospital Of Jining Medical University, Jining, China Address correspondence to Yueqin Chen, Medical Imaging Department, Affiliated Hospital of Jining Medical University, 89 Guhuai Rd, Jining, 272007, China. E-mail: [email protected]Search for more papers by this author First published: 05 July 2024 https://doi.org/10.1002/jum.16520 Zhe Hu and Zhikang Tian contributed equally to this study. The authors declare no competing interests. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References 1Wang SR, Cao CL, Du TT, et al. Machine learning model for predicting axillary lymph node metastasis in clinically node positive breast cancer based on peritumoral ultrasound radiomics and SHAP feature analysis. J Ultrasound Med 2024; 9999:1–15. 10.1002/jum.16483 Web of Science®Google Scholar 2Zhang J, Wei Q, Dong D, Ren L. The role of TPS, CA125, CA15-3 and CEA in prediction of distant metastasis of breast cancer. Clin Chim Acta 2021; 523: 19–25. 10.1016/j.cca.2021.08.027 CASPubMedWeb of Science®Google Scholar 3Ren Z, Yang J, Liang J, et al. Monitoring of postoperative neutrophil-to-lymphocyte ratio, D-dimer, and CA153 in: diagnostic value for recurrent and metastatic breast cancer. Front Surg 2022; 9:927491. 10.3389/fsurg.2022.927491 PubMedWeb of Science®Google Scholar 4Tarighati E, Keivan H, Mahani H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med 2023; 23: 1–16. CASPubMedWeb of Science®Google Scholar Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation