[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"obstetric-ultrasonography\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:obstetric-ultrasonography":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":22,"briefSummary":24,"conditions":25,"keywords":30,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":39,"lastUpdatePostDateStruct":40,"startDateStruct":43,"completionDateStruct":45,"leadSponsor":47,"locationsCount":5},"100623802","clinicians-trust-in-ai-based-fetal-growth-estimates-100623802",false,"NCT07401368","Clinicians' Trust in AI-Based Fetal Growth Estimates","Clinicians' Trust and Decision-Making Using AI-Based Fetal Growth Estimates With and Without Uncertainty: A Randomized Questionnaire Study","Inclusion Criteria:\n\n* Clinicians working in obstetrics and gynecology departments.\n* Regular use of obstetric ultrasound in clinical practice.\n* Willingness to participate in a questionnaire-based study.\n\nExclusion Criteria:\n\n* Clinicians who do not perform obstetric ultrasound examinations.\n* Clinicians with a known conflict of interest related to the AI system being evaluated.",true,"ALL",{"count":19,"type":20},308,"ESTIMATED","INTERVENTIONAL",[23],"NA","This study examines how clinicians trust and use artificial intelligence (AI) when estimating fetal weight during pregnancy.\n\nAccurate assessment of fetal growth is important for identifying growth problems that may affect pregnancy management. New AI-based tools can estimate fetal weight from ultrasound images, but little is known about how clinicians trust these estimates or how uncertainty information influences their decisions.\n\nIn this study, clinicians will review anonymized ultrasound cases and compare fetal weight estimates generated by an AI model with traditional estimates. Some clinicians will also be shown information about the AI model's performance and uncertainty, while others will not.\n\nParticipants will be asked to choose which estimate they find most reliable, indicate their level of confidence, and decide whether they would recommend follow-up scans. The study aims to better understand how AI and uncertainty information affect clinical decision-making and trust among clinicians with different levels of experience.",[26,27,28,29],"Fetal Growth","Obstetric Ultrasonography","Pregnancy","Clinical Decision-making",[31,32,33,34,35,36,37],"Clinical decision-making","Artificial intelligence","Fetal weight estimation","Obstetric ultrasound","Trust","Human-AI interaction","Questionnaire study","NOT_YET_RECRUITING","2026-02-03",{"date":41,"type":42},"2026-02-10","ACTUAL",{"date":44,"type":20},"2026-06-01",{"date":46,"type":20},"2028-12-01",{"name":48,"class":49},"Rigshospitalet, Denmark","OTHER"]