In a recent UK study, researchers have used AI for the first time to measure blood flow and predict chances of death, heart attack and stroke. For the study, which was funded by the British Heart Foundation, researchers took routine Cardiovascular Magnetic Resonance (CMR) scans from more than 1,000 patients at London's St Bartholomew's Hospital and the Royal Free Hospital and used new AI to analyze the images. The AI-assisted approach enabled the researchers to precisely and instantaneously quantify the blood flow to the heart muscle and deliver the measurements to the medical teams treating the patients. "Artificial intelligence is moving out of the computer labs and into the real world of healthcare, carrying out some tasks better than doctors could do alone," said Professor James Moon, of the London-based UCL Institute of Cardiovascular Science and Barts Health NHS Trust. "We have tried to measure blood flow manually before, but it is tedious and time-consuming, taking doctors away from where they are needed most, with their patients."

Artificial intelligence is making its way into health care, and one of its first stops is making sense of all of those scans that doctors order. Already, studies have shown that AI-based tools can, in some cases, pick out abnormal growths that could be cancerous tumors better than doctors can, mainly because digesting and synthesizing huge volumes of information is what AI does best. In a study published Feb. 14 in Circulation, researchers in the U.K. and the U.S. report that an AI program can reliably predict heart attacks and strokes. Kristopher Knott, a research fellow at the British Heart Foundation, and his team conducted the largest study yet involving cardiovascular magnetic resonance imaging (CMR) and AI. CMR is a scan that measures blood flow to the heart by detecting how much of a special contrast agent heart muscle picks up; the stronger the blood flow, the less likely there will be blockages in the heart vessels.

University of Nottingham researchers created an AI system that scanned routine medical data to predict which patients would have strokes or heart attacks within 10 years. The AI system beat the standard method of prediction, correctly making calls in 355 more cases than traditional means. Predicting cardiovascular events like strokes and heart attacks is a notoriously challenging task. In fact, the researchers note in their recent paper that around half of all strokes and heart attacks occur in patients who were never identified as being "at risk." The records included a decade of health outcomes, lab data, drug information, hospital records, and demographic information.

Here at The Human OS, we are slightly obsessed with matchups between artificial intelligence and doctors. In many experiments (though not yet in many clinics), AI systems are showing great promise in diagnosing diseases, analyzing medical images, and predicting health outcomes. They've even performed better than human doctors in certain tasks like surgical stitching and diagnosing autism in infants. Now, in the latest win for AI medicine, researchers at the University of Nottingham in the UK created a system that scanned patients' routine medical data and predicted which of them would have heart attacks or strokes within 10 years. When compared to the standard method of prediction, the AI system correctly predicted the fates of 355 more patients.