“Cardiovascular MRI offers unparalleled image quality for assessing heart structure and function; however, current manual analysis remains basic and outdated,” Manisty said in a statement. “Automated machine learning techniques offer the potential to change this and radically improve efficiency, and we look forward to further research that could validate its superiority to human analysis.”
It’s estimated that around 150,000 cardiac MRIs are performed in the U.K. each year, she said, and based on that number, her team thinks using AI to read scans could mean saving 54 clinician-days per year at every health center in the country.
“Our dataset of patients with a range of heart diseases who received scans enabled us to demonstrate that the greatest sources of measurement error arise from human factors,” Manisty said. “This indicates that automated techniques are at least as good as humans, with the potential soon to be ‘superhuman’—transforming clinical and research measurement precision.”
Credit: Google News