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- ARTIFICIAL INTELLIGENCE

AI tool shows promise in diagnosing advanced heart failure

Applying artificial intelligence techniques to cardiac ultrasound data may make it easier to identify patients with advanced heart failure, a new study has found. The study—led by investigators at Weill Cornell Medicine, Cornell Tech, Cornell Ann S. Bowers College of Computing and Information Science, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian—offers the prospect of better care for many thousands of patients who may be overlooked due to the difficulty of diagnosing their condition.

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AI-powered imaging tracks wound healing under the skin in real time

No matter the size or severity, wounds on human skin are difficult to monitor while they heal. Biopsies disrupt the wound site and are too invasive for routine, repeated monitoring, and most medical imaging devices that could do the job are large, expensive, and booked up with more pressing diagnostics. Clinicians typically resort to visual inspection or quick measurements of the wound’s size over time.

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Deep learning model predicts which heart-failure patients will worsen within a year

Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient’s lungs, legs, feet, and other parts of the body. The condition is chronic and incurable, often leading to arrhythmias or sudden cardiac arrest. For many centuries, bloodletting and leeches were the treatment of choice, famously practiced by barber surgeons in Europe, during a time when physicians rarely operated on patients.

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