{"id":14919,"date":"2025-04-30T13:15:30","date_gmt":"2025-04-30T13:15:30","guid":{"rendered":"https:\/\/dailyai.com\/?p=14919"},"modified":"2025-04-30T13:15:30","modified_gmt":"2025-04-30T13:15:30","slug":"ai-algorithm-predicts-heart-disease-risk-from-bone-scans","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2025\/04\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\/","title":{"rendered":"AI algorithm predicts heart disease risk from bone scans"},"content":{"rendered":"<p><b>Researchers from Edith Cowan University (ECU) and the University of Manitoba have developed an automated program that can identify cardiovascular problems and fall risks from routine bone density scans.\u00a0<\/b><\/p>\n<p><span style=\"font-weight: 400;\">This could make it considerably easier to detect serious health issues before they become life-threatening.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The algorithm, developed by ECU research fellow Dr. Cassandra Smith and senior research fellow Dr. Marc Sim, works by analyzing vertebral fracture assessment (VFA) images taken during standard bone density tests, which are often part of treatment plans for osteoporosis.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">By assessing the presence and extent of abdominal aortic calcification (AAC) in these scans, the program can quickly flag patients at risk of heart attack, stroke, and dangerous falls.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">What&#8217;s truly impressive is the speed at which the algorithm works. While an experienced human reader might take five to six minutes to calculate an AAC score from a single scan, the machine learning program can predict scores for thousands of images in less than a minute.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">That level of efficiency could be a significant benefit for healthcare systems looking to screen large populations for hidden health risks.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The need for such screening is evident. In the <\/span><a href=\"https:\/\/www.ecu.edu.au\/newsroom\/articles\/research\/new-machine-algorithm-could-identify-cardiovascular-risk-at-the-click-of-a-button\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">forskning<\/span><\/a><span style=\"font-weight: 400;\">, Dr. Smith found that a staggering 58% of older individuals who underwent routine bone density scans had moderate to high levels of AAC.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Even more concerning, one in four of those patients were completely unaware of their elevated risk.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;Women are recognized as being under-screened and under-treated for cardiovascular disease,&#8221; Dr. Smith noted. &#8220;This study shows that we can use widely available, low-radiation bone density machines to identify women at high risk of cardiovascular disease, which would allow them to seek treatment.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But the algorithm&#8217;s predictive power doesn&#8217;t stop at heart health. Using the same program, Dr. Sim discovered that patients with moderate to high AAC scores were also at greater risk of fall-related hospitalizations and fractures compared to those with low scores.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;The higher the calcification in your arteries, the higher the risk of falls and fractures,&#8221; Dr. Sim explained. While traditional fall risk factors like previous falls and low bone density are well-known, vascular health is rarely considered.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">&#8220;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.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As with any new technology, there are questions to be answered and challenges to overcome before this kind of AI-assisted screening becomes standard practice.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">First and foremost, the algorithm will need to be validated in larger, more diverse patient populations and integrated seamlessly into existing clinical workflows.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">However, if those challenges can be met, a simple bone scan \u2013 something millions of older adults already undergo regularly \u2013 could become an early warning system for some of the most common and devastating health problems we face.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"<p>Researchers from Edith Cowan University (ECU) and the University of Manitoba have developed an automated program that can identify cardiovascular problems and fall risks from routine bone density scans.\u00a0 This could make it considerably easier to detect serious health issues before they become life-threatening. The algorithm, developed by ECU research fellow Dr. Cassandra Smith and senior research fellow Dr. Marc Sim, works by analyzing vertebral fracture assessment (VFA) images taken during standard bone density tests, which are often part of treatment plans for osteoporosis.\u00a0 By assessing the presence and extent of abdominal aortic calcification (AAC) in these scans, the program<\/p>","protected":false},"author":2,"featured_media":14920,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[],"class_list":["post-14919","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI algorithm predicts heart disease risk from bone scans | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/da\/2025\/04\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI algorithm predicts heart disease risk from bone scans | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers from Edith Cowan University (ECU) and the University of Manitoba have developed an automated program that can identify cardiovascular problems and fall risks from routine bone density scans.\u00a0 This could make it considerably easier to detect serious health issues before they become life-threatening. The algorithm, developed by ECU research fellow Dr. Cassandra Smith and senior research fellow Dr. Marc Sim, works by analyzing vertebral fracture assessment (VFA) images taken during standard bone density tests, which are often part of treatment plans for osteoporosis.\u00a0 By assessing the presence and extent of abdominal aortic calcification (AAC) in these scans, the program\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/da\/2025\/04\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2025-04-30T13:15:30+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2025\/04\/image-21.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1152\" \/>\n\t<meta property=\"og:image:height\" content=\"704\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Sam Jeans\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:label1\" content=\"Skrevet af\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sam Jeans\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimeret l\u00e6setid\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutter\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2025\\\/04\\\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2025\\\/04\\\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\\\/\"},\"author\":{\"name\":\"Sam Jeans\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/person\\\/711e81f945549438e8bbc579efdeb3c9\"},\"headline\":\"AI algorithm predicts heart disease risk from bone scans\",\"datePublished\":\"2025-04-30T13:15:30+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2025\\\/04\\\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\\\/\"},\"wordCount\":475,\"publisher\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2025\\\/04\\\/ai-algorithm-predicts-heart-disease-risk-from-bone-scans\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/image-21.png\",\"articleSection\":[\"Ethics &amp; 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