Use of Artificial Intelligence for Clinical Assessment of Assisted Reproductive Techniques and IVF Outcomes

Part of paid clinical trials in New York, New York.

Sponsor
Weill Medical College of Cornell University
Study ID
NCT04255615
Status
Recruiting
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Conditions

  • ART
  • Infertility
  • in Vitro Fertilization (IVF)

Eligibility Criteria

Sex
ALL
Age
18 Years - 89 Years
Healthy Volunteers
Accepted

Interventions

  • AI to analyze 3 D ultrasound — OTHER
    AI to assess 3 D ultrasound to assess antral follicle count

Study Details

The use of machine learning techniques using an artificial intelligence tool is proposed to analyze clinical data to predict best possible IVF/ART outcomes. This tool has been utilized to accurately predict embryo quality here at Cornell. Utilizing this tool to assess objective clinical findings and predict outcomes of assisted reproductive techniques is sought, with the ultimate goal of an automated tool to reduce implicit physician bias. Within this goal, using this tool to objectively and accurately assess baseline ovarian reserve at the start of an ART cycle is proposed, using 3D sonography to image the ovary and artificial intelligence tool to objectively identify baseline antral follicle counts.

Key Dates

Start date
Feb 12, 2020
Status verified
Dec 2025
Primary completion
Jan 31, 2029
Completion
Sep 30, 2029

Study Design

Enrollment
4,000 participants (estimated)
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER

Arms

  • Other: 3D Ultrasound with AI
    AI tool to assess antral follicle count using 3 D Ultrasound

Primary Outcome Measure

Number of baseline antral follicle count [ Time Frame: Baseline ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
Weill Cornell MedicineNew YorkNew York10021
Nikica Zaninovic, PhD
[email protected]
646-962-2764
Rodriq Stubbs, NP
[email protected]
646-962-3276
Nikica Zaninovic, PhD (PRINCIPAL_INVESTIGATOR)

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Weill Cornell Medicine· New York, NY

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