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A proactive, data-driven healthcare solution that harnesses the power of AI, IoT, and Machine Learning (ML)
3 min read
Healthcare & Life Sciences
Proof of Concept/conceptual architecture
Every year, in spite of spending something like $3 trillion1 on healthcare (around double that of other developed countries), the USA falls short of their goal. The problem is that managing a busy healthcare organization isn’t just about treating patients anymore. Ever-increasing patient expectations around ehealth, as well as an increasing familiarity with, and understanding of, technological advances, have stepped-up the pressure on all concerned. However, one of the most enduring challenges for the healthcare industry has been managing this transition from reactive (non-technological), to proactive (monitoring, smart watches, etc.) and predictive (using data) healthcare. This is true, particularly, for healthcare insurance companies that focus on two distinct areas:
The Luxoft Super Sensors solution complements the work that you do, streamlining processes and heightening results.
Super sensors are capable of monitoring entire environments and the activity within them, indirectly, without the need for direct instrumentation of objects. These sensors use a single custom plug-in sensor board packed with multiple individual sensors but, crucially (from a privacy point of view), no camera.
Data from each sensor is combined and processed with the help of machine learning (ML) algorithms, and used to infer signals that cannot be measured directly. Deploying multiple sensors in an environment that networks one with the other, creates a Distributed Sensing System. This system uses the power of self-learning algorithms to collect data from home environments, wearables, mobile devices, and external sources (including medical histories). It determines an individual’s behavior patterns, then predicts events and takes action if anything out of the ordinary occurs. The data, again with the use of ML, is abstracted into meaningful representations that the whole population can understand.
The solution integrates data from the home environments of patients, with data from external sources such as weather, pollen counts, plus activity data from wearables and mobile devices, to produce a 3600 health model of their lives.
Here at Luxoft, we are building AI and ML algorithms that could help providers anticipate patient behaviors as well as monitor their actual behavior via IoT devices. However, when it comes to digital disruption in healthcare, this is just the tip of the iceberg!
Thanks to IoT, AI, and ML, Luxoft’s solution helps:
These are just a handful of the new opportunities made possible by the combined value and performance of AI, edge processing, and IoT that Luxoft delivers to help the healthcare industry achieve business outcomes through innovation.
