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Development and cloud deployment of machine learning models for heartbeat classification on data from wearable devices — Ikaro Silva (MC10)

Electrical heart signals are one of the most recorded and stored physiological data in healthcare. With cardiovascular diseases being the single most common cause of death in the world, automatic analysis of cardiac signals under normal ambulatory conditions is expected to play a crucial role in assisting clinicians identify health issues. A critical step towards this goal is the automatic classification of heartbeats. The purpose of this work is to showcase the development and deployment of a cloud system for heartbeat classification collected from wearable devices.


Dr. Ikaro Silva is a Data Scientist at MC10 Inc and is responsible for developing algorithms that process the biological signals collected through MC10's unique wearable form factors. Dr. Silva is also a research scientist at MIT, where he is involved in augmenting PhysioNet's open source software and research.

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