The model, described in a study published in the journal Nature Medicine, helps solve the problem of determining whether a patient is having a heart attack when the ECG results are not entirely clear to the doctor. It detects subtle ECG signs that are sometimes difficult to detect even for professionals, which improves risk assessment and allows you to quickly provide the necessary assistance.
The model was developed based on the ECGs of more than 7,000 patients, outstripping existing methods for assessing heart disease.
He correctly stratified patients with chest pain into low, intermediate, and high risk categories. Researchers are currently working to optimize the distribution of the model.
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Source: Ferra
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