Published on in Vol 10, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29398, first published .
A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation

A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation

A Deep Learning Approach to Refine the Identification of High-Quality Clinical Research Articles From the Biomedical Literature: Protocol for Algorithm Development and Validation

Wael Abdelkader 1, MSc, MD;  Tamara Navarro 1, MLiS;  Rick Parrish 1, Dip T;  Chris Cotoi 1, BEng, EMBA;  Federico Germini 1, 2, MSc, MD;  Lori-Ann Linkins 2, MSc, MD;  Alfonso Iorio 1, 2, MD, PhD;  R Brian Haynes 1, 2, MD, PhD;  Sophia Ananiadou 3, 4, BA, DEA, PhD;  Lingyang Chu 5, BSc, PhD;  Cynthia Lokker 1, MSc, PhD

1 Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, CA

2 Department of Medicine, McMaster University , Hamilton, ON, CA

3 Department of Computer Science, University of Manchester , Manchester , GB

4 The Alan Turing Institute , London , GB

5 Department of Computing and Software, Faculty of Engineering, McMaster University, Hamilton, ON, CA

Corresponding Author:

  • Cynthia Lokker, MSc, PhD
  • Health Information Research Unit
  • Department of Health Research Methods, Evidence, and Impact
  • McMaster University
  • 1280 Main St W, CRL-137
  • Hamilton, ON
  • CA
  • Phone: 1 9055259140 ext 22208
  • Email: lokkerc@mcmaster.ca