Imperial College London

Professor the Lord Darzi of Denham PC KBE FRS FMedSci HonFREng

Faculty of MedicineDepartment of Surgery & Cancer

Co-Director of the IGHI, Professor of Surgery
 
 
 
//

Contact

 

+44 (0)20 3312 1310a.darzi

 
 
//

Location

 

Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Liu:2020:10.1136/bmj.m3164,
author = {Liu, X and Rivera, SC and Moher, D and Calvert, MJ and Denniston, AK and Ashrafian, H and Beam, AL and Chan, A-W and Collins, GS and Darzi, A and Deeks, JJ and ElZarrad, MK and Espinoza, C and Esteva, A and Faes, L and Di, Ruffano LF and Fletcher, J and Golub, R and Harvey, H and Haug, C and Holmes, C and Jonas, A and Keane, PA and Kelly, CJ and Lee, AY and Lee, CS and Manna, E and Matcham, J and McCradden, M and Monteiro, J and Mulrow, C and Oakden-Rayner, L and Paltoo, D and Panico, MB and Price, G and Rowley, S and Savage, R and Sarkar, R and Vollmer, SJ and Yau, C},
doi = {10.1136/bmj.m3164},
journal = {BMJ: British Medical Journal},
title = {Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension},
url = {http://dx.doi.org/10.1136/bmj.m3164},
volume = {370},
year = {2020}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines for reporting randomised trials. Its widespread use has been instrumental in ensuring transparency when evaluating new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes.The CONSORT-AI extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI. Both guidelines were developed through a staged consensus process, involving a literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed on in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants).The CONSORT-AI extension includes 14 new items, which were considered sufficiently important for AI interventions, that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and providing analysis of error cases.CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer-reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
AU - Liu,X
AU - Rivera,SC
AU - Moher,D
AU - Calvert,MJ
AU - Denniston,AK
AU - Ashrafian,H
AU - Beam,AL
AU - Chan,A-W
AU - Collins,GS
AU - Darzi,A
AU - Deeks,JJ
AU - ElZarrad,MK
AU - Espinoza,C
AU - Esteva,A
AU - Faes,L
AU - Di,Ruffano LF
AU - Fletcher,J
AU - Golub,R
AU - Harvey,H
AU - Haug,C
AU - Holmes,C
AU - Jonas,A
AU - Keane,PA
AU - Kelly,CJ
AU - Lee,AY
AU - Lee,CS
AU - Manna,E
AU - Matcham,J
AU - McCradden,M
AU - Monteiro,J
AU - Mulrow,C
AU - Oakden-Rayner,L
AU - Paltoo,D
AU - Panico,MB
AU - Price,G
AU - Rowley,S
AU - Savage,R
AU - Sarkar,R
AU - Vollmer,SJ
AU - Yau,C
DO - 10.1136/bmj.m3164
PY - 2020///
SN - 0959-535X
TI - Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension
T2 - BMJ: British Medical Journal
UR - http://dx.doi.org/10.1136/bmj.m3164
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000570245200002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://www.bmj.com/content/370/bmj.m3164
UR - http://hdl.handle.net/10044/1/85760
VL - 370
ER -