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Researchers from Edith Cowan College (ECU) are growing a man-made intelligence algorithm that may use bone density scans captured to detect potential backbone fractures to estimate visceral fats ranges, offering a fast, painless and reasonably priced detection methodology.
“Ever heard of the sneaky fat that hides deep inside your belly and wraps around your organs? That’s visceral fat—a real troublemaker that is strongly linked to serious health problems like heart disease, diabetes, and cancer,” stated Ph.D. pupil Arooba Maqsood.
“Weight problems poses a severe menace to international well being and is a number one explanation for morbidity and mortality worldwide. Past its toll on well being, the financial burden is staggering, putting immense pressure on well being care methods and nationwide economies alike.
“For Australia, the economic cost was A$39 billion in 2019, projected to reach A$228 billion by 2060, which is 3.5% of Australia’s gross domestic product. And it’s not just about money—it is estimated there are 3.7 million obesity-related deaths each year globally,” Maqsood stated.
The harmful visceral fats wrapped round your organs is at present estimated utilizing strategies reminiscent of physique mass index, waist circumference, and waist-to-hip ratio. Nevertheless, Maqsood famous that these measures have limitations, and don’t distinguish between several types of physique fat.
“This oversimplification contributes to inconsistencies in assessment of obesity and its complications, highlighting the need for a more precise approach to measure obesity,” she added.
“Although imaging techniques like MRI and CT scans can accurately measure visceral fat, their hefty price tag is often a limiting factor. And CT also exposes patients to higher levels of radiation.”
Lateral backbone Twin-energy X-ray Absorptiometry (DXA) scans are used to determine backbone fractures. These pictures could be repurposed for opportunistic screening for visceral fats, giving us new and priceless well being insights with out the necessity for further exams.
ECU is coaching its machine studying algorithm on these scans to precisely predict the quantity of visceral fats current in an individual just by lateral backbone DXA scans.
“The machine-learning model has been trained on thousands of images; the next step is to incorporate further datasets from around the world, so it learns from the largest, most diverse cohort possible and becomes as effective as possible,” stated Dr. Syed Zulqarnain Gilani, a senior lecturer and lead AI scientist at ECU.
Maqsood will likely be presenting her analysis on the Worldwide Convention on Medical Picture Computing and Pc Assisted Interventions (MICCAI 2025) held in Korea, September 23–27.
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Machine studying to assist determine ‘hidden fats’ on routine bone scans (2025, September 5)
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