Design and implementation of a radiomic-driven intelligent dental hospital diversion system utilizing multilabel imaging data.

ABSTRACT:

Background

With the increasing burden of dental diseases and the limited availability of healthcare resources, traditional triage methods are inadequate in efficiently utilizing healthcare resources and meeting patient needs. The aim of this study is to develop an advanced triage system that combines oral radiomics and biological multi-omics data, which enables accurate departmental referral of patients by automatically interpreting biological information in oral X-ray images.

Methods

Using a multi-label learning algorithm, we analyzed multi-omics data from 3,942 patients with oral diseases from three cohorts between July 1, 2023 and August 18, 2023, and continuously monitored classification accuracy (ACC) metrics.

Results

In the test cohort and external validation co

SUBMITTER: Wu Y 

PROVIDER: S-EPMC11662546 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature