New AI Method Offers Faster, Safer Visceral Fat Assessment - A Key to Preventing Serious Disease
PERTH, AUSTRALIA – A groundbreaking new method for assessing dangerous visceral fat – the fat that accumulates deep within the abdomen and surrounds vital organs - is being developed by researchers at Edith Cowan University (ECU) in Australia. This innovative approach promises a faster,more accessible,and safer way to identify individuals at risk of heart disease,type 2 diabetes,and even certain cancers.
Visceral fat is increasingly recognized as a important health risk, far beyond simply being a cosmetic concern. Unlike subcutaneous fat, which lies just under the skin, visceral fat actively contributes to inflammation and metabolic dysfunction.
Currently,estimating visceral fat levels relies on methods like Body Mass Index (BMI),waist circumference,and waist-to-hip ratio. However, these measurements have limitations, failing to accurately differentiate between various types of body fat and often leading to inconsistent obesity assessments. More precise imaging techniques, such as MRI and CT scans, are available, but are costly and, in the case of CT scans, involve exposure to radiation.
The ECU team is tackling these challenges with a refined machine learning algorithm. This algorithm analyzes existing spinal scans taken using Dual-Energy X-ray Absorptiometry (DXA) – a common and readily available technique used to assess bone density. By “reading” these scans, the AI can accurately predict visceral fat levels without requiring any additional testing.
“Our automatic learning model has been trained on thousands of images,” explains Syed Zulqarnain Gilani, Senior Lecturer and Principal Researcher at ECU. “The next step is to incorporate datasets from around the globe, allowing the algorithm to learn from a larger and more diverse population and maximize its efficiency.”
This advancement represents a significant step forward in preventative healthcare. By providing a fast, affordable, and non-invasive method for assessing visceral fat, doctors will be better equipped to identify at-risk individuals and implement timely interventions to mitigate the dangers associated with this “hidden” fat.
Source: AGERPRES (via Jurnalul.ro)
SEO Keywords: visceral fat, abdominal fat, heart disease, diabetes, cancer, DXA scan, bone density, machine learning, artificial intelligence, obesity, health risk, preventative healthcare, Edith Cowan University, ECU, health technology.