How Big Data And Machine Learning Can Predict And Prevent Isolated Cases Of Disease

Sanket Shah Thought Leadership

Predicting when and where disease will occur would be of great assistance to medical professionals and public health officials, who could more aggressively focus public awareness campaigns and other programs on certain populations to inhibit the development and spread of measles, or other potentially deadly viruses. In fact, the World Health Organization’s risk assessment tool has been successfully used to guide and strengthen measles elimination program activities by helping officials identify areas failing to meet their measle vaccination targets.

But more difficult to predict are the isolated instances spread across many states. For that kind of predictive power, you need access to BIG DATA.

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Sanket Shah, MSHI is a senior director at BHI He has over a decade of progressive experience as an executor with a history of scaling and driving brand positioning of complex analytic solutions in growth-oriented environments, mature, and emerging verticals. In addition to his role with BHI, he serves as a Clinical Assistant Professor at the University of Illinois-Chicago with graduate courses focused on healthcare data, knowledge management, consumer informatics, and business intelligence.