A system 'SSCAR' that predicts the risk of cardiac arrest with the power of AI will be developed
A system that uses AI to predict the risk of cardiac arrest has been developed by a research team
Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart | Nature Cardiovascular Research
https://doi.org/10.1038/s44161-022-00041-9
AI predicts if and when someone will experience cardiac arrest | Hub
https://hub.jhu.edu/2022/04/07/trayanova-artificial-intelligence-cardiac-arrhythmia/
According to the research team, cardiac arrest associated with arrhythmias accounts for 20% of all deaths worldwide. In fact, many people have died from sudden cardiac arrest, such as 'heart disease' being ranked high in the cause of death ranking in Japan. Patients diagnosed with arrhythmia can reduce the risk of cardiac arrest by using a defibrillator, but many people die unaware of the risk of arrhythmia. Therefore, the research team has developed a system ' Survival Study of Cardiac Arrhythmia Risk (SSCAR) ' that calculates the risk of arrhythmia using AI in order to help detect the risk at an early stage.
SSCAR's AI trains heart images of hundreds of arrhythmia patients and can detect signs of arrhythmia that cannot be determined with the naked eye. In addition, AI that trains 22 items of data such as patient age, weight, race, and prescription drugs is also available, and by using two types of AI, the risk of arrhythmia in the examinee can be evaluated.
As a result of conducting SSCAR tests at 60 medical facilities in the United States, it was possible to evaluate the risk of arrhythmia more accurately than the diagnosis of a doctor. 'SSCAR has the potential to make significant clinical decisions about arrhythmia risk and is the first step in bringing AI to predict patient behavior,' said Natalia Trayanova, a professor at Johns Hopkins University. ..
In addition, according to Professor Trayanova, diagnosis using AI can be applied to fields other than arrhythmia, which depends on visual diagnosis. The research team plans to develop a system to detect heart diseases other than arrhythmia.
Related Posts:
