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Incremental Healthcare Analytics: from analysing health history to planning health future

Nitin Agarwal (Impetus Technologies)
Sponsored Sessions Provincetown

In our day-to-day life, we routinely talk about ‘Financial History’ and ‘Financial Future’. However, we are not equally emphatic about our ‘health future’. This talk attempts to fill up that gap. We will present an incremental healthcare analytics scenario – how can we achieve incremental analytics in patient care? Say that the patients’ data gets updated with a new lab report. How will this impact the prediction we can make about his health? Based on the current ‘health history’ what is the patient’s ‘health future’? What are appropriate short term ‘health goals’ to a desired ‘health future’? How to convert those ‘health goals’ into practical and actionable daily ‘health tasks’? This type of conversation needs to be added to our daily life.
Patients and physicians can be given access to both, the historic health records and predictions. Analysis can be used to generate health goals (e.g. desired levels of sugar to reduce risk). Thus instead of just looking at “health history”, one can also plan for “health future”.
The analytics needs to be performed in real-time so that critical care patients can get quick advice. The real-time part may also be useful in the health exchanges that are going to come up as a result of Obama care.

We present a framework and a set of algorithms that are implemented over Spark Streaming (the real-time variation of the Spark product from UC Berkeley) and Storm from Twitter. Fundamental ideas in this talk are from a patent pending (Indian Patent office – 1148/CHE/2013) real-time analytics platform built by the authors.

The takeaways from the talk for the audience will be # Incremental healthcare analytics use case.

  1. Implementation of machine learning algorithms over Spark/Storm with code sketches.
  2. An integrated framework to convert “health history” to actionable “health tasks” for desired health goals" and “health future”.

Sponsored by Impetus

Nitin Agarwal

Impetus Technologies

Nitin has a PhD in Operations Research and has wide experience of working in both industry and academia. He is currently working as a Head of Data Science Practice at Impetus Technologies where he oversees a team of highly qualified data scientists to solve data science problems in big data.

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