While AI may increase speed and efficiency of medical care on the front lines, one of its most powerful benefits is the ability to search vast amounts of data to learn about genetic aspects of various diseases. Cardiomegaly Is An Enlargement Of The Heart Due To Dilatation Of The Heart Cavities. Earlier identification of persons at risk for heart failure or a genetic cardiomyopathy is a prime example. This could enable persons to be more closely monitored by health care providers and even placed on lists for transplant before they decompensate and develop heart failure leading to cardiogenic shock, which can be ultimately be fatal if not treated and identified in a timely fashion. Researchers at Queen Mary University of London have now harnessed the power of AI to identify patients who are at risk for heart failure, enabling earlier identification, management and treatment of these high-risk individuals.

Genetic research led by Queen Mary University of London could open the way to earlier identification of people at risk of heart failure and to the development of new treatments. The Queen Mary University of London team applied an artificial intelligence (AI) technique to analyse the heart MRI images of 17,000 healthy UK Biobank volunteers. They found that genetic factors accounted for 22-39 per cent of variation in the size and function of the heart's left ventricle, the organ's main pumping chamber. Enlargement and reduced pumping function of the left ventricle can lead to heart failure. The research, which was part-funded by the Wellcome Trust and the British Heart Foundation and published today in the journal Circulation, suggests that genetic factors significantly influence the variation in heart structure and function.

Artificial intelligence has been embraced for its ability to offer insight from big data. By applying the technology to genetics, a research team led by Queen Mary University of London has found clues that they say could aid the development of new drugs for heart failure and identify people at risk of the disease. Based on an AI analysis of heart MRI images from 17,000 volunteers in UK Biobank, the researchers linked genetic factors to 22% to 39% of abnormalities in the size and function of the heart's left ventricle, which pumps blood into the aorta. They published the findings in the journal Circulation. The team identified or confirmed 14 regions in the human genome that play a part in determining the size and function of the left ventricle, because they contain genes that regulate the early development of heart chambers and the contraction of heart muscle.