To give clinicians a quick, cross-sectional look into potential blockages of the heart's major arteries, Abbott has combined digital imaging technology with artificial intelligence to build an automated system for cardiac procedures. The company's Ultreon software relies on catheters equipped with optical coherence tomography, which uses laser light to scan the interior of a blood vessel and the immediately surrounding tissues to detect calcium and plaque deposits, while also instantly measuring the diameter of an artery. The system--which has now received a CE Mark in Europe--is designed to provide surgeons with prompt information during the placement of coronary stents, faster and more precisely compared to conventional angiography imaging. A previous study by Abbott found having the information from OCT scans readily available led most physicians to change their treatment approach, by selecting the proper stent size and placement location. RELATED: FDA clears PhotoniCare's handheld OCT scanner for checking ear infections After planning a procedure using angiography alone, 88% of operations altered course when surgeons saw high-resolution OCT images and automatic measurements from inside the patient's arteries.
The healthcare AI market is projected to reach $34 billion worldwide by 2025, according to Tractica, and this momentum is creating both fear and excitement about its role in the years to come. While one school of thought worries that artificial intelligence may render physicians' jobs as obsolete, others believe that it will only be an asset to the industry. I subscribe to the second school of thought: Artificial intelligence will never replace doctors, but rather will serve as a tool to help them achieve greater results. In 2019, the partnership between AI and humans in the healthcare industry will become more mainstream, as more physicians investigate and adopt the technologies utilizing artificial intelligence in their hospitals to witness the impact of AI on their own practice. As an industry today, we've just begun to realize the tremendous potential AI has to transform the way physicians deliver high-quality, cost-effective, diagnostic and treatment services.
A medical implant that slowly dissolves into the body could be the answer to long-standing safety concerns with devices used to treat clogged arteries. Abbott Laboratories' newly-approved Absorb stent comes with one important caveat: it hasn't yet been shown to be safer than older metal implants. The Food and Drug Administration approved the device Tuesday for patients with coronary artery disease, the artery-narrowing condition that causes about 370,000 U.S. deaths each year, according to government figures. The new stent is made of a plastic-like material that's designed to gradually dissolve over three years. Currently-available stents are permanent, mesh-wire tubes that hold open arteries after a procedure used to clear fatty plaque.
Advances in artificial intelligence (AI) are happening at a much quicker pace than anyone could have predicted. This emerging technology is now being used by businesses and is even finding its way into consumer products. One industry that has fully embraced AI is healthcare and doctors and other hospital staff are using advanced machine learning algorithms to solve problems in new ways. TechRadar Pro spoke with HeartFlow's Founder and Chief Technology Officer Charles A. Taylor to learn more about how the company is using deep learning to build 3-D models of patients' hearts to provide doctors with a safer and more effective way of diagnosing cardiovascular disease. HeartFlow has pioneered technology to help clinicians diagnose coronary heart disease (CHD).
ABBOTT PARK, Ill., Sept. 12, 2019 -- Abbott announced that new research, published in the journal Circulation, found its algorithm could help doctors in hospital emergency rooms more accurately determine if someone is having a heart attack or not, so that they can receive faster treatments or be safely discharged.1 In this study, researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand looked at more than 11,000 patients to determine if Abbott's technology developed using artificial intelligence (AI) could provide a faster, more accurate determination that someone is having a heart attack or not. The study found that the algorithm provided doctors a more comprehensive analysis of the probability that a patient was having a heart attack or not, particularly for those who entered the hospital within the first three hours of when their symptoms started. "With machine learning technology, you can go from a one-size-fits-all approach for diagnosing heart attacks to an individualized and more precise risk assessment that looks at how all the variables interact at that moment in time," said Fred Apple, Ph.D., Hennepin HealthCare/ Hennepin County Medical Center, professor of Laboratory Medicine and Pathology at the University of Minnesota, and one of the study authors. "This could give doctors in the ER more personalized, timely and accurate information to determine if their patient is having a heart attack or not." A team of physicians and statisticians at Abbott developed the algorithm* using AI tools to analyze extensive data sets and identify the variables most predictive for determining a cardiac event, such as age, sex and a person's specific troponin levels (using a high sensitivity troponin-I blood test**) and blood sample timing.