Clinical Informatics News May 13, 2019
Thinking about artificial intelligence (AI) has changed dramatically over time and has become about as hard to describe as art, says Jeff Fried, director of product management for data management company InterSystems. Machine learning (ML) is commonly considered a subset of AI—often a necessary component, in fact—but also encompasses methodologies such as logistic regression once referred to simply as statistics.
The data is in any case “much more important than the algorithms, which are pretty much the same as they were 20 years ago,” says Fried. Data scientists spend most of their time choosing, gathering, combining, structuring, and organizing data so an algorithm can generate meaningful patterns.
While the volume of digital healthcare data has grown exponentially, Fried says, accessing...