Applying machine learning to live patient data

Joseph Blue and Carol Mcdonald walk you through a reference application that processes ECG data encoding using HL7 with a modern anomaly detector, demonstrating how combining visualization and alerting enables healthcare professionals to improve outcomes and reduce costs and sharing lessons learned from their experience dealing with real data in real medical situations.

The business of healthcare in the 21st century is all about reducing costs without sacrificing quality of care. Traditional methods for analyzing health-related data have reached a plateau, but businesses are developing data platforms to leverage challenging data sources to produce new insights and incremental savings. It’s time to stop talking about the promise of big data and start delivering. Joseph Blue and Carol Mcdonald walk you through a streaming system to detect anomalies in data from a heart monitor transported using HL7, demonstrating how data from the monitor flows to an auto-encoder model that compares signals in the context of recent history to detect irregular heartbeats in near real time. Joseph and Carol explain how combining visualization and alerting enables healthcare professionals to improve outcomes and reduce costs and share lessons learned from their experience dealing with real data in real medical situations.