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Use of Artificial Intelligence for Clinical Assessment of Assisted Reproductive Techniques and IVF Outcomes
The Use of Artificial Intelligence for Clinical Assessment of Assisted Reproductive Techniques and IVF Outcomes
Who can join
Ages 18 to 89 · All sexes · Healthy volunteers welcome
Full eligibility criteria
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
About the study
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.
What is being tested
- AI to analyze 3 D ultrasound (other)
Sponsor: Weill Medical College of Cornell University · Participants: 4,000 · Started: Feb 12, 2020
Contact the study team
- Nikica Zaninovic, PhD · Phone: 646-962-2764
- Rodriq Stubbs, NP · Phone: 646-962-3276
Official record on ClinicalTrials.gov — NCT04255615
Locations in the U.S.
| New York | Weill Cornell Medicine, New York |
Conditions
From ClinicalTrials.gov, data retrieved Sep 30, 2026. Each study sets its own eligibility; the study team decides who can join.