Analysis Group Team Publishes Law360 Article on Machine-Learning Algorithms in Health Care Litigation

June 09, 2016

Machine-learning algorithms are used to detect complex, often unforeseen patterns within rich datasets. Although perhaps best known for their use by technology-driven organizations such as Netflix, Amazon, and Google to deliver tailored recommendations to consumers, they are also used in many other industries, including by scientists to identify and target gene mutations and drug therapy, and by doctors to improve treatment outcomes and assist with early disease detection.

In the litigation context, machine learning has been used to improve efficiency and accuracy in e-discovery and fraud detection, to name just two examples. This article by Analysis Group Vice Presidents Lisa Pinheiro and Jimmy Royer, Economist Nick Dadson, and Managing Principal Paul Greenberg provides an overview of how machine learning works, and examines the wide array of potential uses of machine-learning algorithms in the health care litigation context.

Read the article