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Application of Deep Learning to Jointly Assess Embryo Development to Improve Pregnancy Outcome of Embryo Transfer

NCT05671601 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2023-01-04

No results posted yet for this study

Summary

Aim of this research is to apply the deep learning automation based on Time-lapse imaging to jointly assess embryo development，so that it can ensure the consistency of embryo evaluation and improve the accuracy of evaluation.

Conditions

  • Reproductive Medicine

Interventions

DIAGNOSTIC_TEST

Automatic picture recognition

A machine that processes photographs automatically taken

DIAGNOSTIC_TEST

Manual Assessment Group

Manual recognition of pictures

Sponsors & Collaborators

  • The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

    lead OTHER

Eligibility

Min Age
20 Years
Max Age
40 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-12-30
Primary Completion
2023-12-15
Completion
2024-06-15
FDA Device
Yes

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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 NCT05671601 on ClinicalTrials.gov