Publication:
Can artificial intelligence models provide reliable medical counselling to fertility patients?

dc.contributor.coauthorAlcalay, I.
dc.contributor.coauthorWeissman, A.
dc.contributor.coauthorGaner Herman, H.
dc.contributor.coauthorTsafrir, A.
dc.contributor.coauthorFriedman, M.
dc.contributor.coauthorWeiner, E.
dc.contributor.coauthorOrvieto, R.
dc.contributor.coauthorPolyzos, N.P.
dc.contributor.coauthorDahan, M.H.
dc.contributor.coauthorPolyakov, A.
dc.contributor.coauthorFischer, R.
dc.contributor.coauthorEsteves, S.C.
dc.contributor.coauthorFranasiak, J.M.
dc.contributor.coauthorMizrachi, Y.
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorAta, Mustafa Barış
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2026-07-02T07:02:31Z
dc.date.available2026-03-27
dc.date.issued2026
dc.description.abstractResearch question: Can generative artificial intelligence (AI) models provide reliable counselling to fertility patients regarding real-world clinical questions? Design: In this cross-sectional study, 12 clinical questions were developed to reflect common, real-life dilemmas encountered during fertility workup and treatment. Responses to each question were generated by two experienced fertility specialists, and two AI models – ChatGPT and Gemini. Eight leading internationally recognized fertility experts, blinded to the source of each reply, independently rated all the responses on a scale from 1 (strongly disagree) to 10 (strongly agree). Ratings were compared across all four repliers using non-parametric statistical tests. Results: The replies authored by physicians received significantly higher overall scores than those generated by AI models (P < 0.001). The median scores were highest for Doctor A (9.0), followed by Doctor B (8.0), then ChatGPT (7.0) and finally Gemini, which received the lowest score (4.5). The proportion of high-scoring responses (≥8) was greatest for Doctor A (70.8%), followed by Doctor B (56.3%), then ChatGPT (47.9%) and finally Gemini (35.4%) (P < 0.001). Conclusions: Experienced fertility specialists outperformed generative AI models in providing accurate responses to complex clinical questions. Despite the growing accessibility and sophistication of AI tools, their use for individualized fertility counselling remains limited. Continued refinement and clinical validation of AI tools are essential before they can be considered reliable for patient-specific guidance. At present, AI should be viewed as a complementary resource rather than a substitute for expert clinical judgement. © 2025
dc.description.fulltextN/A
dc.description.harvestedfromManual
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessN/A
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.versionPublished version
dc.identifier.WoSQuartileQ1
dc.identifier.doi10.1016/j.rbmo.2025.105237
dc.identifier.eissn1472-6491
dc.identifier.embargoNo
dc.identifier.issn1472-6483
dc.identifier.issue2
dc.identifier.pubmed41475300
dc.identifier.scopus2-s2.0-105026983328
dc.identifier.urihttps://doi.org/10.1016/j.rbmo.2025.105237
dc.identifier.urihttps://hdl.handle.net/20.500.14288/32791
dc.identifier.volume52
dc.identifier.wos001659468900001
dc.keywordsArtificial intelligence
dc.keywordsAssisted reproductive technology
dc.keywordsCounselling
dc.keywordsExperts
dc.keywordsFertility
dc.languageeng
dc.publisherElsevier
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofReproductive BioMedicine Online
dc.relation.openaccessN/A
dc.rightsN/A
dc.rights.uriN/A
dc.subjectObstetrics and gynecology
dc.titleCan artificial intelligence models provide reliable medical counselling to fertility patients?
dc.typeJournal Article
dspace.entity.typePublication
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