Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Dec 5, 2021
Date Accepted: Mar 15, 2022
Date Submitted to PubMed: Mar 17, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

Dhombres F, BONNARD J, BAILLY K, MAURICE P, PAPAGEORGHIOU A, Jouannic JM

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

J Med Internet Res 2022;24(4):e35465

DOI: 10.2196/35465

PMID: 35297766

PMCID: 9069308

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Artificial Intelligence: 20 years of contributions reported in Obstetrics and Gynecology journals

  • Ferdinand Dhombres; 
  • Jules BONNARD; 
  • Kévin BAILLY; 
  • Paul MAURICE; 
  • Aris PAPAGEORGHIOU; 
  • Jean-Marie Jouannic

ABSTRACT

The objective of this study was to provide a systematic review to establish the actual contributions of Artificial Intelligence (AI) reported in Obstetrics and Gynecology (OG/GYN) discipline journals. All publications in OB/GYN core disciplines journals were considered among citations indexed in PubMed with “artificial intelligence” and at least one of the following MeSH terms: "obstetrics", “gynecology”, “reproductive techniques, assisted” or "pregnancy", between 01/01/2000 and 04/30/2020. Publications with application of AI processes were selected and mapped to OB/GYN domains. We reviewed all AI methods, algorithms, datasets, contributions and validation methods. Our PubMed search retrieved 579 citations and 66 publications met the selection criteria. Both Machine Learning methods (n=39/66) and Knowledge Base methods (n=25/66) were represented. Machine Learning used imaging, numerical and clinical datasets. Knowledge Base methods used mostly omics datasets. Contributions of AI were method/algorithm development (53%), hypothesis generation (42%) or software development (3%). Validation was performed on only 1 dataset in most cases (87%) and no external validation was reported. Overall, in journals of our discipline, preliminary work in AI applied to OB/GYN is reported and clinical validation remains an unmet prerequisite. Improvement driven by new AI research guidelines is expected. However, these guidelines are covering only a part of AI approaches reported in this review, hence updates need to be considered.


 Citation

Please cite as:

Dhombres F, BONNARD J, BAILLY K, MAURICE P, PAPAGEORGHIOU A, Jouannic JM

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

J Med Internet Res 2022;24(4):e35465

DOI: 10.2196/35465

PMID: 35297766

PMCID: 9069308

Per the author's request the PDF is not available.