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Cloud-based AI Multimodal Cephalopelvic Model: Development and Promotion of Cephalopelvic Disproportion Prediction and Full-process Labor Monitoring System

Cloud-based AI Multimodal Cephalopelvic Model: Development and Promotion of Cephalopelvic Disproportion Prediction and Full-process Labor Monitoring System

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117989
Enrollment
Unknown
Registered
2026-01-30
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-02-02

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

Conditions

Dystocia due to cephalopelvic disproportion, prolonged labor (including prolonged first stage and prolonged second stage), and arrested labor.

Interventions

test group:None

Sponsors

Women’s Hospital, Zhejiang University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age = 18 years; 2.with a term, singleton pregnancy in cephalic presentation (gestational age = 37+0 weeks).

Exclusion criteria

Exclusion criteria: 1.Stillbirth or major fetal anomalies; 2.absolute contraindications to vaginal delivery.

Design outcomes

Primary

MeasureTime frame
Mode of delivery;—

Secondary

MeasureTime frame
Maternal and neonatal complications;—

Countries

China

Contacts

Public ContactBaihui Zhao

Women’s Hospital, Zhejiang University School of Medicine

zhaobh@zju.edu.cn+86 571 87061501

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026