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Revolutionizing Heart Health Monitoring
Imagine a tool that could swiftly identify potential cardiovascular risks just by analyzing routine bone density scans. Researchers from Edith Cowan University (ECU) have developed an automated machine learning program that does just that. By evaluating vertebral fracture assessment (VFA) images of older women, this innovative algorithm assesses abdominal aortic calcification (AAC)—an important indicator of heart health.
Speeding Up Diagnosis
Normally, healthcare professionals would spend around five to six minutes analyzing each image to assess AAC. However, this machine learning program can process thousands of images in under a minute. Dr. Cassandra Smith, a research fellow at ECU, found that nearly 58% of older individuals screened during routine bone density testing exhibited moderate to high levels of AAC. Alarmingly, one-quarter of these patients were unaware of their elevated risks for heart attack and stroke.
Empowering Women’s Health
This study highlights a critical gap in cardiovascular screening: women are often under-screened and under-treated for heart disease. The algorithm not only aids in identifying those at risk during routine testing, but it also empowers women to seek necessary medical care. As Dr. Smith points out, "People who have AAC don’t present any symptoms, making screening crucial." By integrating this technology in clinical settings, more patients can receive the diagnosis they need to manage their cardiovascular health effectively.
Addressing Fall Risks
The implications of high AAC scores extend beyond cardiovascular risks. According to Dr. Marc Sim, senior research fellow at ECU, individuals with notable AAC levels also face a heightened risk of falls and fractures—a revelation that could alter how healthcare professionals approach elderly care. He states, "Our analysis uncovered that AAC was a very strong contributor to falls risks and was actually more significant than other factors that are clinically identified as falls risk factors." This insight emphasizes the need to consider vascular health when evaluating the overall well-being of older patients.
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