Machine learning-based dynamic prediction of lateral lymph node metastasis in patients with papillary thyroid cancer.

ABSTRACT:

Objective

To develop a web-based machine learning server to predict lateral lymph node metastasis (LLNM) in papillary thyroid cancer (PTC) patients.

Methods

Clinical data for PTC patients who underwent primary thyroidectomy at our hospital between January 2015 and December 2020, with pathologically confirmed presence or absence of any LLNM finding, were retrospectively reviewed. We built all models from a training set (80%) and assessed them in a test set (20%), using algorithms including decision tree, XGBoost, random forest, support vector machine, neural network, and K-nearest neighbor algorithm. Their performance was measured against a previously established nomogram using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), precis

SUBMITTER: Lai SW 

PROVIDER: S-EPMC9589512 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature