Abstract
Cardiology Both children and adults can have cardiac problems. Congenital problems predominate in childhood, whereas adults are more likely to suffer from conditions associated with age. In both cases, however, accurate diagnosis depends on access to health care and the availability of trained specialists. In two recent studies, Arnaout et al. and Yao et al. showed how machine learning can supplement specialist care in both pediatric and adult cardiology settings. Arnaout et al. analyzed fetal ultrasound images to detect congenital heart disease. Yao et al. used machine learning in conjunction with electrocardiogram imaging to detect adults with low ejection fraction (a measure of the amount of blood that the heart succeeds in pumping), which is a risk factor for subsequent heart failure. In each case, the technology should help to improve diagnostic accuracy and access to appropriate treatment. Nat. Med. 27 , 815, 882 (2021).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.