2025 WCHRI Summer Student

An AI tool could speed up diagnosis for kids with wrist and elbow injuries

Justin Kim’s research focused on a new way to diagnose bone fractures in children using handheld ultrasound devices and artificial intelligence. The goal was to see if this technology would be faster and safer than traditional X-rays.

He scanned children who came to the emergency department at the Stollery Children’s Hospital with suspected wrist fractures and compared the AI’s interpretation to a doctor’s diagnosis and X-ray results. The project also assessed how the AI tool influenced doctors’ decision-making.

“One valuable piece of advice is to not be afraid of rejection. For every patient we have to scan, we must acquire consent from the parents/guardians, and it can be discouraging when you’re rejected. That’s part of informed research, and as a result, I have become more confident in talking to parents and children before and while ultrasound scanning!”

Goals:

• Evaluate the accuracy and feasibility of using AI-aided point-of-care ultrasound to diagnose pediatric wrist and elbow injuries.
• Compare the AI-driven interpretations to traditional clinician diagnoses.
• Assess the AI tool’s impact on clinical workflows in the emergency department.

Potential impact: If successful, this research could lead to a faster, non-invasive way to diagnose children’s injuries, potentially reducing wait times in ERs and limiting children’s exposure to radiation from X-rays and other scans.

Supervisor: Jacob Jaremko, professor, Department of Radiology & Diagnostic Imaging

Funder: Stollery Children’s Hospital Foundation

Interested in doing research to improve the health of women and/or children? Read more about WCHRI’s training awards for students at all levels and generous grants for researchers.