Artificial intelligence supports literature screening in medical guideline development: towards up-to-date medical guidelines

Abstract

In a time of exponential growth of new evidence supporting clinical decision making, combined with a labor-intensive process of selecting this evidence, there is a need for methods to speed up current processes in order to keep medical guidelines up-to-date. The purpose of this study was to evaluate the performance and feasibility of active learning to support the selection of relevant publications within the context of medical guideline development.