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Clinical study on the application of computer-aided diagnosis using deep convolution neural network in the diagnosis of esophageal squamous cell carcinoma

Clinical study on the application of computer-aided diagnosis using deep convolution neural network in the diagnosis of esophageal squamous cell carcinoma

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000035999
Enrollment
Unknown
Registered
2020-08-21
Start date
2020-12-01
Completion date
Unknown
Last updated
2020-08-31

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

Conditions

Esophageal squamous cell carcinoma

Interventions

Gold Standard:Pathology
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Sponsors

West China Hospital, Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: From December 2020 to December 2021, all patients underwent painless gastroscopy on a mainframe of Endoscopy Center of West China Hospital.

Exclusion criteria

Exclusion criteria: (1) There were no contraindications for painless gastroscopy or biopsy; (2) there were any other conditions that the researchers considered unsuitable to participate in this study.

Design outcomes

Primary

MeasureTime frame
Accuracy of computer-aided diagnosis system in the detection of esophageal squamous cell carcinoma;—

Countries

China

Contacts

Public ContactHu Bing

West China Hospital, Sichuan University

hubingnj@163.com+86 18980601278

Outcome results

None listed

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