Prospective Diagnostic Accuracy and Technical Feasibility of Artificial Intelligence-Assisted Rib Fracture Detection on Chest Radiographs: Observational Study.

ABSTRACT:

Background

Rib fractures are present in 10%-15% of thoracic trauma cases but are often missed on chest radiographs, delaying diagnosis and treatment. Artificial intelligence (AI) may improve detection and triage in emergency settings.

Objective

This study aims to evaluate diagnostic accuracy, processing speed, and technical feasibility of an artificial intelligence-assisted rib fracture detection system using prospectively collected data within a real-world, high-volume emergency department workflow.

Methods

We conducted an observational feasibility study with prospective data collection of a faster region-based convolutional neural network-based AI model deployed in the emergency department to analyze 23,251 real-world chest radiographs (22,946 anteroposterior; 305 o

SUBMITTER: Huang ST 

PROVIDER: S-EPMC12854400 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature