Background/Objective: Rib fractures are one of the most specific fractures in child abuse and are among the most common identified. Diagnosis of an unsuspected rib fracture in a young child or infant is highly concerning for child abuse. Given rib fractures, particularly acute rib fractures, can be subtle and difficult for even experienced radiologists to identify, a screening diagnostic tool to improve the detection accuracy would provide significant value. The objective of this investigation is to create a machine learning algorithm with the ability to recognize the presence or absence of rib fractures on chest radiographs in pediatric patients less than 3 years old. Read More

Meeting name: SPR 2023 Annual Meeting & Postgraduate Course , 2023

Authors: Satoor Vamsish, Marine Megan

Keywords: Machine learning, Chest x-ray, Pediatric