28 September 2025
New research released today from the Royal Australasian College of Physician’s Journal of Paediatrics and Child Health indicates that artificial intelligence (AI) could soon transform how doctors diagnose hip dysplasia in children across Australia and around the world.
The systematic review, the largest ever of its kind, was conducted by experts from the University of Western Australia and found that AI is on par with diagnostic accuracy of clinical experts, and makes its diagnoses 30 times faster.
The review examined 23 studies from across the world using AI to interpret over 15,000 medical images of children from birth to 10 years of age.
Dr Suketu Bhavasr (Child and Adolescent Health Services, Perth, Western Australia) and Dr Chandra Rath (PhD, University of Western Australia), authors of the study say “Detecting the condition early is essential, but diagnosis relies on expert interpretation of pelvic x-rays and ultrasound scans, which can be time-consuming and relies on doctor availability.
“Developmental hip dysplasia affects between one to three per cent of infants and, if left untreated, can cause lifelong health issues including early arthritis, spinal curvature and chronic back pain.”
It is estimated that around 3,000 infants in Australia are diagnosed every year, and thousands more being screened.
“The research indicates the potential for AI to help relieve clinical workloads and improve access to early screening, particularly in certain countries or remote areas where trained specialists are in short supply.
“In one trial, lightly trained primary care staff using portable ultrasound and AI support achieved detection rates comparable to experts.
“Artificial intelligence offers significant potential to automate manual tasks, ensure service consistency, and improve patient care.
“Despite its promise, the technology is not without hurdles. Diagnostic accuracy drops with poor-quality images, and differences in patient age and image angles.”
The findings show that AI has the potential to deliver expert-level accuracy, increase diagnostic efficiency, reduce healthcare disparities, and make early diagnosis more accessible in areas where doctors are less available.