Assessing Demographic Biases in Deep Learning Model for Fetal Growth Estimation in Clinical Practice. Patients Eligible for Inclusion Are Women with a Gestational Age Between 24-42 Weeks Undergoing a Third-trimester Growth Scan. the Image Data from the Scan Are Used to Calculate Fetal Weight.

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

185 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-07-01

Study Completion Date

2024-11-30

Brief Summary

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The goal of this observational study is to compare a new artificial intelligence (AI) feedback tool with the traditional method for estimating fetal weight during ultrasound scans on pregnant women between 24-42 weeks of gestation. The study aims to investigate the presence of demographic bias in the AI model. The demographic factors examined in the study include Body Mass Index (BMI), the number of births, fetal age, mother\'s age, fetal sex, and the presence of preeclampsia. Moreover, the study will compare the accuracy of the AI model and the Hadlock model, a fetal growth formula, in estimating fetal weight. Participants will have their ultrasound scans pseudonymized and securely stored on password-protected removable drives, ensuring their identity and privacy are maintained. Afterward, the ultrasound data will be sent to the Technical University of Denmark (DTU), where the AI model will analyze the images to estimate fetal weight.

Detailed Description

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Conditions

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Pregnancy Complications

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Pregnant women between 24-42 weeks of gestation

No interventions

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Women with gestational age between 24-42 weeks undergoing a third-trimester growth scan.

Exclusion Criteria

* Women with multiple pregnancies.

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Responsible Party

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Julie Leth-Petersen

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Copenhagen University Hospital, Rigshospitalet

Copenhagen, , Denmark

Site Status

Countries

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Denmark

References

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Salomon LJ, Alfirevic Z, Da Silva Costa F, Deter RL, Figueras F, Ghi T, Glanc P, Khalil A, Lee W, Napolitano R, Papageorghiou A, Sotiriadis A, Stirnemann J, Toi A, Yeo G. ISUOG Practice Guidelines: ultrasound assessment of fetal biometry and growth. Ultrasound Obstet Gynecol. 2019 Jun;53(6):715-723. doi: 10.1002/uog.20272.

Reference Type BACKGROUND

PMID: 31169958 (View on PubMed)

Other Identifiers

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p-2024-15469

Identifier Type: -

Identifier Source: org_study_id