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Relevant Projects

Photo of Yael Yaniv
Associate Professor
Advanced AI methods to meed the need of clinicians

Within this project we developed a set of deep-learning tools that enabled design of a robust, trustworthy, explainable, and transparent system, while retaining the superior level of performance expected of deep learning-based algorithms for classification of heart conditions from short ECG recordings collected using a two-lead device.

Advanced AI methods to identify heart conditions

Within this project we developed an app which integrates an AI method that can automatically distinguish between atrial fibrillation, other rhythm disturbances and noise when using a mobile one-lead ECG device. In parallel we developed an automated AI-based system to identify heart conditions from 12-lead digital or image ECG recordings with high accuracy. We also demonstrated that the images scanned using a smartphone provided the same accuracy as machine images.