Development and validation of an interpretable machine learning model for prediction of occult lymph node metastasis in clinical stage T1 lung adenocarcinoma

We developed an interpretable ML model that accurately predicts the risk of OLNM using readily available data. This tool facilitates personalized surgical decision-making, potentially guiding the extent of lymph node dissection (LND) to avoid overtreatment in low-risk patients while ensuring adequate staging and resection in high-risk individuals.