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Abstract #1118

A meta-analysis of the diagnostic performance of machine learning–based MRI for axillary lymph node metastasis in breast cancer patients

Chen Chen1, Fabao Gao1, and Xiaoyue Zhou2
1Department of Radiology, West China Hospital, Chengdu, China, 2MR Collaboration, Siemens Healthineers Ltd., Shanghai, China

Axillary lymph node dissection (ALND) is the gold standard for evaluating axillary lymph node metastasis (ALNM), but ALND may not confer a survival advantage. Therefore, reliable, noninvasive approaches for preoperative prediction of ALNM have been needed. The use of machine learning (ML) in predicting ALNM in breast cancer patients has been reported. We have conducted a large-sample-size assessment and a meta-analysis of published studies concerning the diagnostic performance of ML-based MRI in predicting ALNM in breast cancer patients.

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