Pain Relief for Doctors Labelling Data

The paper "Novel artificial intelligence-driven software significantly shortens the time required for annotation in computer vision projects" discusses a study comparing the efficiency of two video annotation tools, Encord and CVAT, in detecting polyps during colonoscopies. The results showed that using Encord led to a 6.4-fold increase in labelling speed compared to CVAT, with most annotators producing more labels with Encord than CVAT. Encord's "embedded intelligence" automated over 96% of the labels produced during the experiment, significantly reducing manual input required for annotation. The study highlights the potential of AI-driven software in saving doctors valuable time and improving medical AI adoption.