AI model for predicting sudden cardiac death more accurate than expected

“We have been working for almost 30 years in the field of SCD prediction, however, we did not expect to reach such a high level of accuracy,” lead author Xavier Jouven, MD, PhD, a professor of cardiology and epidemiology at the Paris Cardiovascular Research Center, said in a statement. “We also discovered that the personalized risk factors are very different between the participants and are often issued from different medical fields (a mix of neurological, psychiatric, metabolic and cardiovascular data) – a picture difficult to catch for the medical eyes and brain of a specialist in one given field. While doctors have efficient treatments such as correction of risk factors, specific medications and implantable defibrillators, the use of AI is necessary to detect in a given subject a succession of medical information registered over the years that will form a trajectory associated with an increased risk of sudden cardiac death.”

For AI-powered risk assessments to work, the researchers noted, consistency would be required from one EHR to the next; an algorithm trained to extract data from one resource may not be reliable if using input from a completely difference resource.  

Read the full abstract here.

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