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AI-Driven Model Impact on Patient Engagement in Medically Assisted Reproduction

NCT07087171 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 774

Last updated 2026-02-23

No results posted yet for this study

Summary

Infertility is a globally significant medical condition, profoundly impacting individuals and couples both emotionally and physically. The multifaceted nature of in vitro fertilization (IVF) treatment demands active patient participation, with engagement playing a pivotal role in treatment success and satisfaction. However, suboptimal engagement can lead to challenges such as not initiating treatment, missed appointments, medication errors, dropping out and heightened stress levels, all of which may adversely affect clinical outcomes.

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized healthcare, offering innovative solutions for personalized patient care. In IVF, AI-ML models hold the potential to enhance patient engagement by delivering tailored communication, reminders, and educational support, but also improved prognostication by providing personalized and accurate predictions of treatment outcomes. These capabilities enable patients to make more informed decisions and enhance their adherence to treatment protocols.This protocol outlines a prospective evaluation of an AI-ML model, specifically the Univfy PreIVF report, developed to improve patient engagement in IVF care. Recently, a retrospective, multicenter study reported improved IVF utilization rates among patients counselled using the Univfy PreIVF Report. The current study will prospectively assess the model's effectiveness in addressing individual patient needs and creating a supportive treatment environment. Specifically, this study will measure adherence to providers' recommendation of treatment protocols. By analyzing the impact of these interventions, this research aims to provide robust evidence for the integration of AI-ML technologies in reproductive medicine, paving the way for broader implementation and improved patient outcomes.

Conditions

  • Infertility (IVF Patients)
  • Artificial Intelligence (AI)

Interventions

OTHER

Artificial intelligence-Machine learning report with accurate personalized probabilities of having a live birth rate

Patients included in the prospective arm will receive the Univfy® PreIVF Report with their accurate personalized probabilities of having a live birth rate (Univfy®) together with a medical explanation by their physician

Sponsors & Collaborators

  • Univfy Inc.

    collaborator INDUSTRY

  • Instituto Valenciano de Infertilidade de Lisboa

    lead NETWORK

Eligibility

Min Age
18 Years
Max Age
45 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-06-11
Primary Completion
2026-06-30
Completion
2026-08-31

Countries

  • Portugal

Study Locations

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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 NCT07087171 on ClinicalTrials.gov