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

NCT ID: NCT04255615

Last Updated: 2025-12-24

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

RECRUITING

Clinical Phase

NA

Total Enrollment

4000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-02-12

Study Completion Date

2029-09-30

Brief Summary

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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.

Detailed Description

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This study will collect prospective data, specifically 3D transvaginal ultrasound of ovaries at time of baseline evaluation at beginning of an ART cycle. All participants will be asked to give written consent to be included in the study. At the time of initial ultrasound that is routinely done on the first day of the ART cycle, the physician performing the ultrasound will use a 3D ultrasound transvaginal probe to perform the ultrasound and capture both 2D and 3D images. 3D ultrasound is performed routinely for patients undergoing ART and is not an investigative procedure, however is not uniformly performed at the time of the baseline ultrasound. As per standard practice, the baseline antral follicle count will be documented by the performing physician, as well as a 3D image saved to be analyzed later using AI.

Information about the medical history, treatment and outcomes will be collected as part of the study. Data maintained in the medical record as a result of standard of care monitoring for IVF and IUI will also be used for this study. This will include semen analysis (male partners if applicable) and pregnancy outcomes. For male partners, the semen analysis record will be part of the fertility history and semen analysis will be performed as standard of care with semen processing for fertilization. Additional data related to the treatment and outcomes will be collected from the medical record from the time of consent through the end of the treatment (including pregnancy outcomes).

The time commitment for subjects may take up to 1 month (time from consent signing to 3D ultrasound) and to the time of delivery if pregnant (up to 9 months). No further procedures will be performed in the study group.

Conditions

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Infertility in Vitro Fertilization (IVF) ART

Keywords

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Artificial Intelligence

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

OTHER

Blinding Strategy

NONE

Study Groups

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3D Ultrasound with AI

AI tool to assess antral follicle count using 3 D Ultrasound

Group Type OTHER

AI to analyze 3 D ultrasound

Intervention Type OTHER

AI to assess 3 D ultrasound to assess antral follicle count

Interventions

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AI to analyze 3 D ultrasound

AI to assess 3 D ultrasound to assess antral follicle count

Intervention Type OTHER

Other Intervention Names

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z

Eligibility Criteria

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Inclusion Criteria

* All patients undergoing ovarian stimulation (including OI and IVF cycles)
* Treatment for fresh embryo transfer and cryopreservation of oocytes or embryos upfront
* Healthy male partners of the female subjects who agree to be part of the study.

Exclusion Criteria

* None
Minimum Eligible Age

18 Years

Maximum Eligible Age

89 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Weill Medical College of Cornell University

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Nikica Zaninovic, PHD

Role: PRINCIPAL_INVESTIGATOR

Weill Medical College of Cornell University

Locations

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Weill Cornell Medicine

New York, New York, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Nikica Zaninovic, PhD

Role: CONTACT

Phone: 646-962-2764

Email: [email protected]

Rodriq Stubbs, NP

Role: CONTACT

Phone: 646-962-3276

Email: [email protected]

Facility Contacts

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Nikica Zaninovic, PhD

Role: primary

Rodriq Stubbs, NP

Role: backup

Other Identifiers

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19-06020306

Identifier Type: -

Identifier Source: org_study_id