Insight Report 14 minutes PremiumHow Machine Learning Can Help Identify Adverse Drug Reactions Coresight Research January 30, 2018 Executive SummaryIn this report, we explore how machine learning can help identify the possibility of adverse drug reactions (ADRs). More than half of Americans regularly take prescription drugs—four of them on average—and 75% of Americans take at least one over-the-counter drug regularly. About 53% of Americans who use prescription drugs get them from more than one provider and 35% state that a healthcare provider has never reviewed their medication to see if they could stop taking it. Annually, US hospital emergency rooms see more than1 million people for ADRs. More than a quarter of these patients need to be admitted for further treatment. Machine-learning algorithms, such as the Apriori algorithm, can run through vast, unstructured data sets of medications, conditions, drug effects, patient histories, and other variables, and calculate the probability of an ADR, to a certain degree. This report is for paying subscribers only. Already a paying subscriber? Please log in to see the entire report.If you wish to learn more about our subscription plans and become a paying subscriber, click here. This document was generated for Other research you may be interested in: What Do US Consumers Think About Generative AI?Weekly US and UK Store Openings and Closures Tracker 2024, Week 13: Five Below Announces US Store Expansion PlansRetail-Tech Landscape—Food TechnologyUS Store Tracker Extra, August 2023: Retailers To Open 78 Million Square Feet of New Retail Space This Year