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NCT06765512
Artificial Intelligence-Based Machine Learning to Diagnose and Classify Adenomyosis from Ultrasound Scans: a Multicentre Model Development Study
trial testing use of deep learning and automated machine learning to diagnose and classify adenomyosis in Adenomyosis of Uterus in 10,000 participants. Participants enrolled and being followed up; not accepting new ones.
4 December 2025
Quick facts
| Lead sponsor | CARE Fertility UK |
|---|---|
| Status | Active, enrolled |
| Study type | OBSERVATIONAL |
| Enrollment | 10,000 |
| Start date | 4 June 2024 |
| Primary completion | 4 December 2025 |
| Estimated completion | 6 February 2026 |
| Sites | 1 location across United Kingdom |
Drugs / interventions tested
- use of deep learning and automated machine learning to diagnose and classify adenomyosis
Conditions studied
- Adenomyosis of Uterus — all drugs for Adenomyosis of Uterus →
Sponsor
CARE Fertility UK
Who can join
Eligibility, female only, with Adenomyosis of Uterus. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The aim of this study is to use the vast dataset of annotated ultrasound images of normal uterus and of adenomyosis of varying severity to train a neural network using deep learning framework (Pytorch) and automated machine learning tool (Vertex AI). The main question it aims to answer are: 1. Diagnostic performance of automated (Google Vertex AI (Artificial intelligence) vision) and deep learning (Pytorch) machine learning model 2. Time saved in assessment of adenomyosis per healthcare professional
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06765512
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
Related trials
Other recruiting trials for Adenomyosis of Uterus
Currently open trials in the same condition.
- NCT07478614 — Multicenter Observational Cohort Study on the Epidemiology of Therapeutic Strategies in Patients Affected by Adenomyosis · recruiting
- NCT07465822 — The Learning Curve of a Gynecology and Obstetrics Resident Performing Vaginal Natural Orifice Transluminal Endoscopic Su · active not recruiting
- NCT07397715 — Association of Ultrasound Features of the Myometrium Suggestive of Adenomyosis and Clinical Symptoms · recruiting
Other CARE Fertility UK trials
Trials by the same sponsor.
- NCT05418140 — Adenomyosis and Pregnancy Outcomes in Women Undergoing Assisted Reproductive Technology Treatment · active not recruiting
- NCT04170517 — Serum Progesterone Levels on the Day of Frozen Embryo Transfer (FET) and Pregnancy Outcomes · completed
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 NCT06765512 (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 CARE Fertility UK
- Last refreshed: 9 January 2025
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/NCT06765512.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing