Publication:
Artificial intelligence, clinical decision support algorithms, mathematical models, and calculator applications in infertility: a systematic review and hands-on digital applications

dc.contributor.coauthorBulletti C., Franasiak J.M., Busnelli A., Sciorio R., Berrettini M., Aghajanova L., Bulletti F.M.,
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorAta, Mustafa Barış
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2025-03-06T20:59:27Z
dc.date.issued2024
dc.description.abstractThe aim of this systematic review was to identify clinical decision support algorithms (CDSAs) proposed for assisted reproductive technologies (ARTs) and to evaluate their effectiveness in improving ART cycles at every stage vs traditional methods, thereby providing an evidence-based guidance for their use in ART practice. A literature search on PubMed and Embase of articles published between 1 January 2013 and 31 January 2024 was performed to identify relevant articles. Prospective and retrospective studies in English on the use of CDSA for ART were included. Out of 1746 articles screened, 116 met the inclusion criteria. The selected articles were categorized into 3 areas: prognosis and patient counseling, clinical management, and embryo assessment. After screening, 11 CDSAs were identified as potentially valuable for clinical management and laboratory practices. Our findings highlight the potential of automated decision aids to improve in vitro fertilization outcomes. However, the main limitation of this review was the lack of standardization in validation methods across studies. Further validation and clinical trials are needed to establish the effectiveness of these tools in the clinical setting.
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.identifier.doi10.1016/j.mcpdig.2024.08.007
dc.identifier.issn2949-7612
dc.identifier.issue4
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85206154732
dc.identifier.urihttps://doi.org/10.1016/j.mcpdig.2024.08.007
dc.identifier.urihttps://hdl.handle.net/20.500.14288/27712
dc.identifier.volume2
dc.keywordsArtificial intelligence
dc.keywordsClinical decision support algorithms
dc.keywordsMathematical models
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofMayo Clinic Proceedings: Digital Health
dc.subjectMedicine
dc.titleArtificial intelligence, clinical decision support algorithms, mathematical models, and calculator applications in infertility: a systematic review and hands-on digital applications
dc.typeReview
dspace.entity.typePublication
local.publication.orgunit1SCHOOL OF MEDICINE
local.publication.orgunit2School of Medicine
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