One Click Away, Your Health Is Here to Stay  

For once, artificial intelligence will come to your rescue! There are reports that this intelligent tech is now developing the capacity to foresee impending medical problems with the latest uncovering of AI in medical laboratory.

A disorder known as abdominal aortic calcification (AAC) causes the aorta to stiffen up. One of the major arteries that allows blood to flow from the heart to the rest of the body is the aorta.  

AI in medical laboratory will also be able to identify your risk of fractures, dementia in old age, and falls. AAC can be detected by the same devices that can identify osteoporosis, dual-energy x-ray absorptiometry (DXA or DEXA). 

Radiologists and other medical specialists are needed in order to interpret the results of these images. The process takes approximately 5 to 15 minutes per image. 

But scientists and medical and health sciences researchers at Edith Cowan University (ECU) have worked collaboratively to develop software that can analyze scans a great deal faster—roughly 60,000 photos in a single day. 

Software that quickly analyzes bone density scans to find abdominal aortic calcification (AAC), a predictor of cardiovascular events and other health hazards, was developed by Edith Cowan University (ECU) artificial intelligence health researchers. The software processed the photos in 80% agreement with the experts, and it has the potential to completely change how early disease is discovered in ordinary clinical practice. 

These days, a rapid sign of a cardiovascular health risk can be found using a bone density scan. 

The accumulation of calcium deposits in the walls of the abdominal aorta is known as abdominal aortic calcification (AAC). It may signal a higher chance of experiencing cardiovascular events including heart attacks and strokes. 

Save Time = Save Lives

ECU, the University of Washington, the University of Minnesota, Southampton, the University of Manitoba, the Marcus Institute for Aging Research, and Hebrew Senior Life Harvard Medical School collaborated internationally to produce the findings. genuinely a cross-disciplinary, world endeavor. 

The study is the largest of its type, was based on the most widely used bone density machine models and is the initial one to have been validated in a real-world environment utilizing photos acquired as part of normal bone density testing. Although it is not the first algorithm created to assess AAC from these images, it is the largest of its kind. 

It observed over 5000 images that were examined by the team’s algorithms and experts. 

80 percent of the time after comparing the data, the expert and program agreed on the level of AAC low, moderate, or high, which is an outstanding statistic considering it was the software’s first release. 

Importantly, the software mistakenly identified only 3% of individuals with high AAC levels as having low levels. 

This is noteworthy since these people have the most severe disease and are at the greatest risk for both fatal and nonfatal cardiovascular events as well as all-cause mortality, according to Professor Lewis. 

These results are from our version 1.0 algorithm, and we have already significantly improved the results with our most current versions, even if there is still work to be done to increase the software’s accuracy compared to human readings. 

Professor Lewis continued to mention that “Automated assessment of the presence and extent of AAC with similar accuracies to imaging specialists provides the possibility of large-scale screening for cardiovascular disease and other conditions – even before someone has any symptoms.” 

AI in Medical Laboratory and Tech Benefits

According to Dr. Abdulghani Abou Koura at University of Virgina “AI is beneficial because it aids Dr’s in reading the results in a more accurate manner. AI on the other hand is available 24/7 and this will speed up the process of the patients’ results.” 

He continues to add that if AI is programmed by professionals, it would be able to detect the tiniest of details. 

This will make it feasible for those who are at risk to change their lifestyles much earlier and will put them in a better position to be healthier in their later years. 

AI isn’t that bad after all, is it?

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