How oncology is adapting to the rise of artificial intelligence - MedCity News

When it comes to data curation, the problem isn't the rise of Big Data, but the haphazard way data often present themselves. That's how John Quackenbush characterized the issue in a panel Wednesday morning at the MedCity CONVERGE conference in Philadelphia on practical applications of artificial intelligence (AI) and machine learning (ML) in oncology. Quackenbush, the director of the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute in Boston, was referring to the difficulties of faced by curators when they had to go into clinical trial protocol pages and take down the studies' entry criteria manually due to the inconsistent way they were written. "I like to characterize it not as a Big Data problem, but as a messy data problem," he said. Moderator Ayan Bhattacharya, who serves as advanced analytics specialist leader at Deloitte Consulting, noted that health management organizations, health plans and others have been investing in technology to assist curation that had previously been the work of human editors.