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Experts from the Universities of East Anglia, Sheffield, and Leeds have developed a new groundbreaking AI method that improves the accuracy and efficiency of analyzing MRI heart scans. This innovation could provide a way for faster, more accurate, and non-invasive diagnosis of heart failure and other cardiac conditions, thus saving valuable time and resources for the healthcare sector.
According to Innovation News Network, the research team used data from 814 patients at Sheffield and Leeds Teaching Hospitals to train an AI model, which was then tested using scans and data from 101 patients at Norfolk and Norwich University Hospitals to ensure accuracy.
The fact it was trained using data from many different hospitals, various types of scanners, and was tested on a diverse patient group, makes this model stand out. Furthermore, while previous studies focused on the heart’s two main chambers, this model provides a complete analysis of the entire heart.
The study explains that this innovative AI method was comparable to the manual analysis that is traditionally performed by doctors, and could thus lead to much better treatment outcomes.
Leader of the research Dr. Pankaj Garg explained: “The AI model precisely determined the size and function of the heart’s chambers and demonstrated outcomes comparable to those acquired by doctors manually but much quicker… Unlike a standard manual MRI analysis, which can take up to 45 minutes or more, the new AI model takes just a few seconds,” adding that this automated technique could offer speedy and dependable evaluations of heart health, with the potential to enhance patient care.
Looking forward, the researchers said future studies should test the model with larger patient groups from different hospitals, use various types of MRI scanners and include other common diseases in medical practice – all this is meant to determine if the model will perform well in a broader range of real-world situations.
