CASE STUDY | Evariant Speeding up the Predictive Analytics Process with Automated Machine Learning In an increasingly dynamic and competitive healthcare environment, the need is clear: a healthcare organization must grow its business through patient, non-patient, and physician engagement. As healthcare systems balance both volume- to-value-based service delivery and marketing approaches, there is an even greater need to access and leverage all of an organization’s data, analytics, and digital communication assets. A significant piece of capitalizing on these assets requires predictive analytics. Consider, for example, the ability to predict high-risk individuals who would benefit from health screenings, to determine the propensity for certain cancers, or to aid physicians wi

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