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Deep learning algorithm based on artificial intelligence to assist the diagnosis of early esophageal cancer

Deep learning algorithm based on artificial intelligence to assist the diagnosis of early esophageal cancer

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000028822
Enrollment
Unknown
Registered
2020-01-05
Start date
2020-01-13
Completion date
Unknown
Last updated
2020-01-06

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

Conditions

Early esophageal carcer

Interventions

Gold Standard:Routine gastroscopy was performed to observe the results of esophageal mucosal lugoiodine staining and biopsy pathology by endoscopists
rate&#32
of&#32
early&#32
cancer

Sponsors

988th Hospital of Joint Logistic Support Force of PLA
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: (1) Aged 18-75 years; (2) The clinical diagnosis and treatment process produces gastroscopy in patients; (3) Signing the written informed consent.

Exclusion criteria

Exclusion criteria: (1) Patients undergoing emergency examination of upper gastrointestinal due to hematemesis and abdominal pain; (2) With history of other malignant tumors; (3) Pregnancy and lactation; (4) Patients are unable to understand the purpose of this study.

Design outcomes

Primary

MeasureTime frame
Detection rate of esophageal early cancer;

Secondary

MeasureTime frame
Sensitivity, specificity, accuracy, area under the subject operating characteristic curve;

Countries

China

Contacts

Public ContactJin Huang

988th Hospital of Joint Logistic Support Force of PLA

419043875@qq.com+86 13673366093

Outcome results

None listed

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