Provided third phase support to help validate a new artificial intelligence platform called a ‘convolution neural network classifier’. The study evaluated the platform’s performance on various arrhythmias diagnosed on 12-lead ECGs and single-lead Holter monitors. The solution focused on identifying the correct arrhythmia at the time of a significant clinical event, including a cardiac arrest.
This tool aims to automate accurate ECG readings, especially among more sinister arrhythmias, to aid clinicians in their workup of patients lacking access to modern healthcare services.
