protocolSection identificationModule nctId: NCT06371859, orgStudyIdInfo id: 3-3031-2915/1, briefTitle: Human-AI Collaborative Intelligence for Improving Fetal Flow Management, statusModule overallStatus: RECRUITING, startDateStruct date: 2024-04-15, primaryCompletionDateStruct date: 2024-12-01, completionDateStruct date: 2025-12-01, studyFirstPostDateStruct date: 2024-04-17, lastUpdatePostDateStruct date: 2024-04-23, sponsorCollaboratorsModule leadSponsor name: Rigshospitalet, Denmark, class: OTHER, collaborators name: Slagelse Hospital, collaborators name: Technical University of Denmark, descriptionModule briefSummary: This randomized controlled study evaluates the effectiveness of explainable AI (XAI) in improving clinicians' interpretation of Doppler ultrasound images (UA and MCA) in obstetrics. It involves 92 clinicians, randomized into intervention and control groups. The intervention group receives XAI feedback, aiming to enhance accuracy in ultrasound interpretation and medical decision-making.Objectives:1. To develop an interpretable model for commonly used Doppler flows, specifically the Pulsatility Index (PI) of the umbilical artery (UA) and middle cerebral artery (MCA), with the aim to provide quality feedback on Doppler spectrum images and suggest potential gate placements.2. To test the effects of providing Explainable AI (XAI)-feedback for clinicians compared with no feedback on their accuracy in ultrasound interpretation and management., conditionsModule conditions: Healthy, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: RANDOMIZED, interventionModel: PARALLEL, interventionModelDescription: Randomized controlled trial, primaryPurpose: HEALTH_SERVICES_RESEARCH, maskingInfo masking: DOUBLE, maskingDescription: Sealed envelopes will be used and opened at the time of inclusion of each participant. Each participant will be randomized to either AI support or no support. The allocation of participants will be performed by (XYZ) who does not have access to the randomization order., whoMasked: PARTICIPANT, whoMasked: INVESTIGATOR, enrollmentInfo count: 92, type: ESTIMATED, armsInterventionsModule interventions name: "XAI feedback on MCA/UA Doppler spectral curves and gate placement suggestions", outcomesModule primaryOutcomes measure: Responses will be reviewed independently by two fetal medicine sonographers, and in case of disagreement between the two experts, a consensus will be reached., secondaryOutcomes measure: Accuracy of flow image management among competence groups, eligibilityModule sex: ALL, stdAges: CHILD, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: Rigshospitalet, status: RECRUITING, city: Copenhagen, state: Capital Region Of Denmark, zip: 2100, country: Denmark, contacts name: Zahra Bashir, MD, role: CONTACT, contacts name: Zahra Bashir, MD, role: PRINCIPAL_INVESTIGATOR, geoPoint lat: 55.67594, lon: 12.56553, locations facility: Slagelse Hospital, status: RECRUITING, city: Slagelse, state: Region Zealand, zip: 4200, country: Denmark, contacts name: Zahra Bashir, MD, role: CONTACT, contacts name: Zahra Bashir, MD, role: PRINCIPAL_INVESTIGATOR, geoPoint lat: 55.40276, lon: 11.35459, hasResults: False