UofT-JMIR Paper-Peer Reviewer Recommender System

Rapid and open dissemination of research is critical for the advancement of science. Preprint servers (such as MedRxiv, BioRxiv, PsyRxiv, and aRxiv) are becoming increasingly popular in health and medicine to share early research results, particularly in the context of the current COVID-19 pandemic. Given the need for rapid peer review, we need to innovate in rapid prioritization, classification, assignment, and evaluation of research papers (with a focus on medicine). A proposed AI-based method to match STM papers/submissions with suitable reviewers will significantly speed up the review process and improve the quality of feedback provided to the researchers. The proposed approach will also help in identifying the reviewers with similar expertise and interests to build peer-reviewer communities.

Faculty Supervisor:

Eldan Cohen;Michael Guerzhoy

Student:

Partner:

JMIR Publications Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program: