Machine learning and Shapley Additive exPlanations to predict metastasis of lymph nodes posterior to the recurrent laryngeal nerve in cN0 papillary thyroid carcinoma.

ABSTRACT:

Objective

Prophylactic dissection of lymph nodes posterior to the recurrent laryngeal nerve (LN-prRLN) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) remains controversial due to the inability to preoperatively assess LN-prRLN metastasis.

Materials and methods

This study aims to construct and validate an interpretable predictive model for LN-prRLN metastasis in cN0 PTC using machine learning (ML) method. Data were collected from hospital A and divided into training and testing sets (7:3). Additional data from the hospital B were used as validation set. Nine ML models, including XGBoost, were developed. Predictive performance was evaluated using ROC curves, decision curve analysis (DCA), calibration curves, and precision-recall curves. The best model was

SUBMITTER: Zhou J 

PROVIDER: S-EPMC12819197 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature