Stroke prevention through precision diagnosis of atrial fibrillation with an AI model

Purpose and goal:

Zenicor together with two partners (Modulai, Karolinska Hospital) will further develop the next generation AI algorithm for the analysis of ECG plots. With use of ML opens up the possibility of getting more information about the patient´s state of health from an ECG. The project´s potential creates the conditions for an efficient screening program and increased cost-effectiveness and at the same time can reduce suffering and inconvenience for the Swedish and the rest of the world´s population.

Expected results and effects: ** Denna text är maskinöversatt **

With a successful results, the project parties, representing the entire value chain, will be able to commercialize an AI model to analyze ECG curves in aim of determining from the ECG of healthy patients increased risk of (FF) and freeing up time in healthcare facilities for the staff by significantly reducing the need to manually review ECG waveforms.

Approach and implementation: ** Denna text är maskinöversatt **

The project is divided into five work packages. Two of the packages are development of the algorithm itself, one package is to explain the AI model and documentation regarding the algorithm. One package is the clinical study that will verify the algorithm. Based on the clinical study, the regulatory and commercialization package should include the results for the launch of the algorithm to improve stroke prevention.