Condition: Infertility · in Vitro Fertilization (IVF) · ART · Sponsor: Weill Medical College of Cornell University
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.
This description comes directly from the study's public registry record.
Nikica Zaninovic, PhD · 646-962-2764 · nizanin@med.cornell.edu
Rodriq Stubbs, NP · 646-962-3276 · res2011@med.cornell.edu
Always discuss trial participation with your own doctor first.
| Weill Cornell Medicine | New York, New York, United States | Recruiting |
Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.
We email about this public record only. Unsubscribe anytime with one click. Never medical advice.
This page is independently generated by Eichor from the public ClinicalTrials.gov record and re-synced daily. It is not the sponsor's official website unless claimed. Nothing here is medical advice; eligibility is always determined by the study team — talk to your own doctor first.
Source record: clinicaltrials.gov/study/NCT04255615