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Developing an AI-based predictive model for adverse pregnancy outcomes by integrating multimodal data

Developing an AI-based predictive model for adverse pregnancy outcomes by integrating multimodal data

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600116492
Enrollment
Unknown
Registered
2026-01-12
Start date
2026-01-13
Completion date
Unknown
Last updated
2026-01-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Uterine structural injuries

Interventions

Uterine Injury Group:None

Sponsors

Southern Medical University Southern Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Voluntarily sign the informed consent form. 2.Age>=18; 3.Gender: Female; 4.Diagnosis via medical history: scarred uterus (post-cesarean section, post-myomectomy or adenomyomectomy, or post-uterine rupture repair), post-cervical conization, or post-induced abortion. Or diagnosis via hysteroscopy: intrauterine adhesions. 5.Planning pregnancy or currently pregnant.

Exclusion criteria

Exclusion criteria: 1.Diagnosed with a psychiatric disorder and unable to comply with follow-up. 2.Deemed ineligible for the study by the investigator.

Design outcomes

Primary

MeasureTime frame
CompositeLiveBirth Outcome;—

Secondary

MeasureTime frame
Pregnancy Outcomes;Neonatal Outcomes;Pregnancy Complications;—

Countries

China

Contacts

Public ContactShi Yuhua

Southern Medical University Southern Hospital

shiyuhua2003@126.com+86 20 62786842

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026