Machine learning for predicting the prognosis of patients with thymoma and thymic carcinoma.

ABSTRACT:

Background

Thymoma and thymic carcinoma are the most common tumors of the anterior mediastinum. However, there are little research on applying machine learning (ML) approaches to the prognostic prediction of thymoma and thymic carcinoma. The study aims to develop predictive models utilizing ML techniques to accurately forecast the 5-year survival of patients with thymoma and thymic carcinoma.

Methods

Patients with malignant thymic neoplasms were identified in the Surveillance, Epidemiology, and End Results (SEER) 17 database, and their demographic and clinicopathological characteristics were collected. ML classifiers, including elastic net regularized logistic regression, random forest (RF), non-linear support vector machine (SVM), extreme gradient boosting (XGBoost) machine

SUBMITTER: Xu H 

PROVIDER: S-EPMC11898343 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature