UNSW researchers have developed a soft robotic model of the human heart that can mimic disease and provide a realistic environment for testing the next generation of cardiac devices. Researchers at UNSW Sydney have developed a fully synthetic soft robotic heart that reproduces the complex movements and internal structures of the human heart, opening the door to better treatments, safer medical devices and more personalised care. Published in Nature Communications and Advanced Science, the research introduces a beating model of the left side of the heart that includes artificial valves, papillary muscles and chordae tendineae - structures that are critical to healthy heart function and are frequently affected by disease. The device is able to accurately reproduce the process in a real heart where cardiac valves leak and blood flows backwards, which increases the risk of heart failure and other life-threatening complications. In that way, the research team say the new soft robot can eventually help provide a better understanding of heart conditions, reduce reliance on animal testing and provide doctors with patient-specific models to plan treatments before procedures are performed.

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Artificial intelligence in medical care is here to stay -- but it can do more harm than good, especially if those implementing it lose sight of the essential importance of a doctor's clinical judgment. As a primary-care physician, my job is to evaluate and re-evaluate a patient in an ongoing personalized way even the best AI could never attain. Here's an example: An 80-year-old patient of mine with chronic heart failure drank and ate too much on a recent Caribbean cruise and ended up in a hospital, his lungs filled with fluid. A cardiac echo revealed an ejection fraction (how well the heart is pumping) of only 15%. In fact, a recent study concluded AI might have assessed that ejection fraction better than the cardiologist who did so, and this assessment is clearly going to be an important role for AI. But the actual management of the patient went well beyond a simple number.

It would be easy to wonder what Zachi Attia is doing in the cardiac operating rooms of one of America's most prestigious hospitals. He has no formal medical training or surgical expertise. The first time he watched a live procedure, he worried he might faint. But at Mayo Clinic, the 33-year-old machine learning engineer has become a central figure in one of the nation's most ambitious efforts to revamp heart disease treatment using artificial intelligence. Working side by side with physicians, he has built algorithms that in studies have shown a remarkable ability to unmask heart abnormalities long before patients begin experiencing symptoms.

Artificial intelligence can predict better than real doctors when patients with serious heart disorders are likely to die. That's according to a paper published this week in Radiology. A team of medics and computer scientists, led by the MRC London Institute of Medical Sciences (LMS) at Imperial College London, created what is claimed to be the first computer program that uses machine learning to study heart disease. Pulmonary hypertension, a condition that increases the level of pressure exerted on the arteries that supply oxygen to the lungs, is dangerous if left untreated. It affects up to 7,000 people in the UK, and a third of patients die of heart failure within five years of diagnosis.