Development and comparison of machine learning models for predicting moderate-to-severe tinnitus in patients with hearing loss.

ABSTRACT:

Objective

Analyze the psychological and clinical factors of clinically significant tinnitus (THI score ≥38) in patients with hearing loss, construct predictive models based on four machine learning (ML) algorithms, and compare the predictive performance of different models.

Methods

Patients with hearing loss who visited the Department of Otolaryngology at Qinghai University between August 2024 and May 2025 were enrolled in this study. Clinical data were retrieved from the hospital's electronic medical record system. The study outcome was the occurrence of clinically significant tinnitus. Predictive variables were screened using univariate analysis, the least absolute shrinkage and selection operator (LASSO) regression, and the Boruta algorithm. Four ML algorithms-logistic re

SUBMITTER: Zhang C 

PROVIDER: S-EPMC12832511 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature