Accuracy and Efficiency of Machine Learning–Assisted Risk-of-Bias Assessments in “Real-World” Systematic Reviews-Reference-Cited by-同舟云学术

Accuracy and Efficiency of Machine Learning–Assisted Risk-of-Bias Assessments in “Real-World” Systematic Reviews

Published:2022-07 Issue:7 Volume:175 Page:1001-1009
ISSN:0003-4819
Container-title:Annals of Internal Medicine
language:en
Short-container-title:Ann Intern Med

Author:

Arno Anneliese¹^ORCID,Thomas James²^ORCID,Wallace Byron³,Marshall Iain J.⁴^ORCID,McKenzie Joanne E.⁵^ORCID,Elliott Julian H.⁵^ORCID

Affiliation:

1. EPPI-Centre, University College London, London, United Kingdom, and School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia (A.A.)

2. EPPI-Centre, University College London, London, United Kingdom (J.T.)

3. College of Computer and Information Science, Northeastern University, Boston, Massachusetts (B.W.)

4. School of Population Health and Environmental Sciences, King's College London, London, United Kingdom (I.J.M.)

5. School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia (J.E.M., J.H.E.).

Publisher

American College of Physicians

Subject

General Medicine,Internal Medicine

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