A prognostic model for thermal ablation of benign thyroid nodules based on interpretable machine learning.

ABSTRACT:

Introduction

The detection rate of benign thyroid nodules is increasing every year, with some affected patients experiencing symptoms. Ultrasound-guided thermal ablation can reduce the volume of nodules to alleviate symptoms. As the degree and speed of lesion absorption vary greatly between individuals, an effective model to predict curative effect after ablation is lacking. This study aims to predict the efficacy of ultrasound-guided thermal ablation for benign thyroid nodules using machine learning and explain the characteristics affecting the nodule volume reduction ratio (VRR).

Design

Prospective study.

Patients

The clinical and ultrasonic characteristics of patients who underwent ultrasound-guided thermal ablation of benign thyroid nodules at our hospital between

SUBMITTER: Li Z 

PROVIDER: S-EPMC11366643 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature