Use of Artificial Intelligence for Clinical Assessment of Assisted Reproductive Techniques and IVF Outcomes (AI in ART)

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

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.

Study Overview

• Status: Recruiting
• Conditions: Infertility; ART; in Vitro Fertilization (IVF)
• Intervention / Treatment: Other: AI to analyze 3 D ultrasound

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 4000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Rodriq Stubbs, NP; Phone Number: 646-962-3276; Email: res2011@med.cornell.edu
• Study Contact Backup: Name: Nikica Zaninovic, PhD; Phone Number: 646-962-2764; Email: nizanin@med.cornell.edu

Study Locations

• United States
  • New York
    • New York, New York, United States, 10021
      • Recruiting
      • Weill Cornell Medicine
      • Contact: Rodriq Stubbs, NP; Phone Number: 646-962-3276; Email: res2011@med.cornell.edu
      • Contact: Nikica Zaninovic, PhD; Phone Number: 646-962-2764; Email: nizanin@med.cornell.edu
      • Principal Investigator: Nikica Zaninovic, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 89 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: 3D Ultrasound with AI; AI tool to assess antral follicle count using 3 D Ultrasound	Other: AI to analyze 3 D ultrasound; AI to assess 3 D ultrasound to assess antral follicle count; Other Names: z

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of baseline antral follicle count	To assess the accuracy and feasibility of using our artificial intelligence tool to assess antral follicle count, an indicator of baseline ovarian reserve, at time of baseline ultrasound for ART compared to qAVCantral and manual follicle counts to number of total oocytes retrieved.	Baseline
Number of retrieved oocytes	To assess the accuracy and feasibility of using our artificial intelligence tool	2 weeks

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of mature oocytes	Number of mature oocytes (ART cycles)	2 weeks
Number of multiple gestation	Number of multiple gestation for OI cycles.	approximately 6- 8 weeks
Number of clinical intrauterine pregnancies IVF	Clinical intrauterine pregnancies	approximately 6- 8 weeks
Number of clinical intrauterine pregnancies OI	Clinical intrauterine pregnancies	Approximately 6- 8 weeks

Collaborators and Investigators

• Sponsor: Weill Medical College of Cornell University
• Investigators: Principal Investigator: Nikica Zaninovic, PHD, Weill Medical College of Cornell University

Study record dates

Study Major Dates

• Study Start (Actual): February 12, 2020
• Primary Completion (Estimated): January 31, 2029
• Study Completion (Estimated): September 30, 2029

Study Registration Dates

• First Submitted: February 3, 2020
• First Submitted That Met QC Criteria: February 3, 2020
• First Posted (Actual): February 5, 2020

Study Record Updates

• Last Update Posted (Estimated): December 24, 2025
• Last Update Submitted That Met QC Criteria: December 17, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Artificial Intelligence
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Infertility
• Other Study ID Numbers: 19-06020306

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No