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

NCT04255615 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 4000

Last updated 2025-12-24

No results posted yet for this study

Summary

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.

Conditions

Interventions

OTHER

AI to analyze 3 D ultrasound

AI to assess 3 D ultrasound to assess antral follicle count

Sponsors & Collaborators

  • Weill Medical College of Cornell University

    lead OTHER

Principal Investigators

  • Nikica Zaninovic, PHD · Weill Medical College of Cornell University

Study Design

Allocation
NA
Purpose
OTHER
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Max Age
89 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-02-12
Primary Completion
2029-01-31
Completion
2029-09-30

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04255615 on ClinicalTrials.gov