Quarkside

03/06/2013

Predictive Monitoring: Heart Attack and Stroke?

Filed under: Innovation,Risk — lenand @ 6:12 am
Tags: , ,

Machine learning via neural networks produces impressive results.  The Blood Glucose prediction hackathon used three data streams: historical blood glucose, insulin dosage and carbohydrate consumption.  This explains approximately 50% of the prediction.

Blood Glucose Predictive Power

Blood Glucose Predictive Power

Adding three more streams would increase this to 85%; other nutrition, activity and other lifestyle factors.  All these could be simply collected from mobile devices and used in other health prediction applications. It shows the value of monitoring data streams for multiple purposes.  This data could also be analysed alongside logs of blood pressure and heart rhythms.

Just think of the value to people who are at risk of heart attack or stroke.   Real-time predictions of heart rate and blood pressure could set alarms that would moderate a person’s behaviour.  An impertinent machine telling you to Stop driving!, sit down! or have a rest! may upset your plans – but it is better than risking your own or another life.

Machine learning is not rule based – it calculates the rules.

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