09:15
45 mins
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THE POWER OF MACHINE LEARNING IN DIGITAL HEALTH
Maarten De Vos
Abstract: There is currently an exponential growth in numbers and types of connected devices such as tablets, wearables and hand-held devices, that have the potential to revolutionize the amount of data we collect about our health and potentially empower people to live healthier lives. This offers an unprecedented opportunity for consumers to take control of their own health in a highly personalized manner. Despite the enormous potential, there are also still several challenges that have to be dealt with, in particular around compliance, around extracting robust information from noisy datastreams, deriving powerful biosignatures for different diseases and building machine learning models that can predict disease state. We will illustrate how embedded algorithmic power allows to turn different wearable devices into clinical grade systems for improved diagnosis and management of mental health conditions like bipolar disorder, as well as for objective assessment of neurological disorders like Parkinson’s or Multiple Sclerosis.
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