Healthcare, Australia (Commonwealth Union) – Artificial Intelligence (AI) is revolutionizing medicine by enhancing diagnostics, treatment planning, and patient care. AI algorithms, particularly in machine learning, are capable of analyzing vast amounts of medical data with unparalleled accuracy and speed, leading to early disease detection and personalized treatment plans.
Researchers at QIMR Berghofer have created a computer-based “growth chart” poised to revolutionize pediatric brain health monitoring and facilitate earlier detection of neurodevelopmental delays. This adds another area where AI may play a significant role in medicine.
Dr. Nathan Stevenson and Dr. Kartik Iyer, alongside researchers and clinicians from Australia and Finland, developed a non-invasive AI application that charts a child’s brain age by analyzing brain signals as they sleep.
Utilizing an electroencephalogram (EEG) to measure brain activity, the QIMR Berghofer team applied machine learning algorithms to data from 2,000 children from Finland and Australia to develop the growth chart.
Dr. Stevenson stated that this tool could enable clinicians to identify neurological issues earlier, leading to more effective therapeutic actions as well as personalized management.
“Developmental delays affect the health of children and hinder their ability to reach their full potential,” added Dr. Stevenson.
“The European Brain Council and World Health Organisation acknowledge the need for better measures of early brain development. Our brain ‘growth chart’ is one such measure.
“We have mirrored the widespread use of physical growth charts, to create a neurodevelopmental growth chart which facilitates rapid and easy clinical assessment of early-life brain maturation and health.”
Researchers of the study indicated that over 10 percent of children across the globe go through clinically significant neurodevelopmental delays. The primary factors contributing to these delays include prematurity, acquired brain injury, structural brain abnormalities, exposure to toxins, and childhood epilepsies.
Dr. Iyer explained that their innovative tool maps a child’s neurodevelopmental age in comparison to their chronological age, providing a way to monitor brain health over time. Last year, the team utilized similar AI technology on electrocardiogram (ECG) heart monitoring data from preterm infants to offer pediatricians enhanced insights into development. The new brain age tool, however, represents a significant advancement in this technology.
Dr. Iyer indicated that by extracting detailed information from EEG signals, they are able to accurately predict brain age and measure the disparity between this and the specific age of the child. For instance, if the brain age is delayed, it can prompt valuable discussions between clinicians as well as their caregivers regarding the child’s neurodevelopmental progress.
Dr. Jasneek Chawla, who is a Paediatric Respiratory and Sleep Medicine Physician for the Queensland Children’s Hospital, joined hands with the QIMR Berghofer team on the project and described the new tool as an exciting development.
Dr. Chawla indicated that the brain age is one of the most significant measures they have for children. This brain growth chart is a user-friendly tool with the possibility to significantly take further clinicians’ understanding, helping them in the formulation of early intervention strategies and predicting future cognitive status.
The brain “growth chart” was put together for the applications with children from infancy through adolescence.
The project was a collaborative effort with researchers from the University of Helsinki and Queensland Children’s Hospital. It got its backing from the National Health and Medical Research Council (NHMRC) in Australia and appeared in the eBioMedicine publication.
