Using an artificial intelligence tool can be as accurate as human assessors in level one screening for a systematic review

Author:

Burns Joseph K.1ORCID,Etherington Cole1ORCID,Cheng‐Boivin Olivia2,Boet Sylvain1234ORCID

Affiliation:

1. Clinical Epidemiology Program Ottawa Hospital Research Institute Ottawa ON Canada

2. Department of Anesthesiology and Pain Medicine The Ottawa Hospital Ottawa ON Canada

3. Francophone Affairs & Department of Innovation in Medical Education Faculty of Medicine University of Ottawa Ottawa ON Canada

4. Ottawa Hospital Research Institute Ottawa ON Canada

Publisher

Wiley

Subject

Health Information Management,Library and Information Sciences,Health Informatics

Reference24 articles.

1. Feature engineering and a proposed decision‐support system for systematic reviewers of medical evidence;Bekhuis T.;PLoS One,2014

2. Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry;Borah R.;British Medical Journal Open,2017

3. STARD 2015: An updated list of essential items for reporting diagnostic accuracy studies;Bossuyt P. M.;BMJ (Clinical Research Ed.),2015

4. Burns J. K. Etherington N. Cheng‐Boivin O. &Boet S.(2019).Artificial intelligence in systematic reviews. A comparison of automated versus conventional human reference screening. Open Science Framework.https://osf.io/rfch4/

5. Support‐vector networks;Cortes C.;Machine Learning,1995

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