Development and validation of an interpretable machine learning model for predicting the risk of distant metastasis in papillary thyroid cancer: a multicenter study.

ABSTRACT:

Background

The survival rate of patients with distant metastasis (DM) of papillary thyroid carcinoma (PTC) is significantly reduced. It is of great significance to find an effective method for early prediction of the risk of DM for formulating individualized diagnosis and treatment plans and improving prognosis. Previous studies have significant limitations, and it is still necessary to develop new models for predicting the risk of DM of PTC. We aimed to develop and validate interpretable machine learning (ML) models for early prediction of DM in patients with PTC using a multicenter cohort.

Methods

We collected data on patients with PTC who were admitted between June 2013 and May 2023. Data from 1430 patients at Yunnan Cancer Hospital (YCH) served as the training and intern

SUBMITTER: Hou F 

PROVIDER: S-EPMC11567106 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature