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In a recent survey of life sciences executives, 95% of respondents said they expect to use machine learning in the coming years to analyze real world data. While many life sciences organizations have started to implement machine learning algorithms and invest in advanced analytics, there’s still a fair amount of uncertainty around it, its potential, and the best ways to employ.

This white paper will cover:

  • Current state of machine learning analytics in life sciences organizations
  • Why machine learning is becoming an essential tool in the analytics toolbox for epidemiology teams
  • The best machine learning analytics use cases for epidemiology teams