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NCT05671601
Application of Deep Learning to Jointly Assess Embryo Development to Improve Pregnancy Outcome of Embryo Transfer
trial testing Automatic picture recognition in Reproductive Medicine in 100 participants. Status unknown.
15 December 2023
Quick facts
| Lead sponsor | The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School |
|---|---|
| Status | Status unknown |
| Study type | OBSERVATIONAL |
| Enrollment | 100 |
| Start date | 30 December 2022 |
| Primary completion | 15 December 2023 |
| Estimated completion | 15 June 2024 |
Drugs / interventions tested
- Automatic picture recognition
- Manual Assessment Group
Conditions studied
- Reproductive Medicine — all drugs for Reproductive Medicine →
Sponsor
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Who can join
Adults 20 to 40, female only, with Reproductive Medicine. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT05671601
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT05671601 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
- Last refreshed: 4 January 2023
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05671601.
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