Dr Bydon- Using Machine Learning to Personalize Remote Patient Monitoring (RPM) Systems Dr. Mohammed Bydon - Using Machine Learning to Personalize Remote Patient Monitoring (RPM) systems A faculty team at ASU is currently developing a hardware-based machine learning system that can learn from high-speed, high-dimensional streaming data on Internet of Things (IoT). The ASU team did a presentation at Mayo Clinic, Arizona on Dec. 2 and talked about the potential use of the proposed technology (hardware-based machine learning from streaming data) on remote patient monitoring (RPM) devices to create personal profiles of individual patients from streaming data generated by a variety of body sensors. There was a consensus among the Mayo Clinic attendees (both in Scottsdale/Phoenix and Rochester) to move ahead and collaborate with ASU on potential use of this technology. Subsequent discussions were held with Mayo Clinic physicians in Rochester (Dr. Mohamad Bydon and his neurosurgery group) and Jacksonville (Dr. Charles Bruce) on specific potential applications to target initially. Preventice, a company that manufactures, sells and services a RPM device called BodyGuardian, was also involved in these discussions (http://www.preventicesolutions.com/). The BodyGuardian technology was developed at Mayo Clinic by Dr. Charles Bruce and others and licensed to Preventice.
|Effective start/end date||6/24/17 → 8/2/17|
- Mayo Clinic Rochester: $2,911.00
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