Authors: Manya Sharma
Abstract: Healthcare analytics plays a pivotal role in extracting meaningful insights from vast amounts of healthcare data to improve patient outcomes, reduce costs, and enhance overall healthcare delivery. In this paper, we focus on Bayesian inference as a powerful statistical tool in healthcare analytics and compare it with the traditional frequentist approach. We explore the advantages and disadvantages of each method, providing a comprehensive analysis of their applications in healthcare settings. Additionally, we present practical examples and discuss the implications of choosing one approach over the other in different healthcare scenarios.
Keywords: Bayesian Inference, Frequentist Approach, Healthcare Analytics Statistical Paradigms, Data Interpretation, Prior Information, Clinical Trials Diagnostic Testing
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