Deep learning diagnosis of adult tibial plateau fractures: multicenter study with external validation.

ABSTRACT:

Purpose

To evaluate a MobileNetV3-YOLOv8 deep learning (DL) model for detecting tibial plateau fractures (TPFs), including occult TPFs (OTPFs), on knee radiographs. We hypothesized that the DL model would improve diagnostic performance and reduce interpretation time, particularly for less experienced physicians.

Materials and methods

This retrospective, multicenter study, included 1543 adult patients from 5 tertiary hospitals in China. A total of 3547 radiographs were included: 2837 for training/validation and 710 from a single external center for testing. In the test set, 267 (37.6%) were normal, 282 (39.7%) were obvious TPFs, and 161 (22.7%) were OTPFs. Performance metrics comprised sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive va

SUBMITTER: Huo T 

PROVIDER: S-EPMC12429206 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature