Construction of a prediction model for axillary lymph node metastasis in stage cN0 hormone receptor-positive breast cancer: based on interpretable machine learning methods

Key Points

• Axillary lymph node metastasis prediction significantly aids preoperative assessment, enhancing individualized treatment plans.
• The KNN model delivered favorable performance with interpretability scores, including detailed insights for clinical use.
• Assessment using interpretable machine learning methods provides a clear framework for risk prediction in breast cancer cases.
• Highlights the importance of personalized treatment strategies, emphasizing clinical applicability in ongoing patient care.

Abstract