The Continuous Active Learning (CAL®) Tool for Rapid Evidence Reviews is an innovative platform created to improve the efficiency and accuracy of evidence synthesis reviews.
Traditional citation screening can be a time-consuming and labour-intensive process, especially when working with thousands of search results. The CAL® Tool addresses this challenge by incorporating machine learning techniques that adapt based on your screening decisions, helping prioritize relevant studies and reduce workload.
This project is the result of a collaboration between researchers at the University of Waterloo and the Knowledge Translation Program at St. Michael’s Hospital, part of Unity Health Toronto.
CAL® was developed by Dr. Gordon V. Cormack (Professor Emeritus, University of Waterloo), Dr. Maura R. Grossman (Research Professor, University of Waterloo). The collaboration effort producing this version of the tool, adapted for rapid evidence synthesis, was led by Dr. Andrea Tricco (Unity Health Toronto, University of Toronto) and the Knowledge Translation Program.
By combining clinical expertise with cutting-edge AI research, the CAL® Tool represents a step forward in enabling evidence-based healthcare decisions and research.
Our goal is to make rapid evidence review screening more accessible and efficient for researchers, clinicians, and students worldwide.