Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

ABSTRACT:

Introduction

Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial intelligence (AI) tools to assist fracture detection in adult patients exist, although their efficacy in children is less well known. This study aims to evaluate whether a commercially available AI tool (certified for paediatric use) improves healthcare professionals (HCPs) detection of fractures, and how this may impact patient care in a retrospective simulated study design.

Methods and analysis

Using a multicentric dataset of 500 paediatric radiographs across four body parts, the diagnostic performance of HCPs will be evaluated

SUBMITTER: Shelmerdine SC 

PROVIDER: S-EPMC11628946 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature