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Automated Diagnosis of Esophageal Squamous Cell Carcinoma Under Narrow Band Imaging Using a Deep Learning Model

Automated Diagnosis of Precancerous Lesion and Superficial Esophageal Squamous Cell Carcinoma Under Narrow Band Imaging Using a Deep Learning Model

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000030888
Enrollment
Unknown
Registered
2020-03-16
Start date
2020-03-11
Completion date
Unknown
Last updated
2020-03-23

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

Conditions

esophageal cancer

Interventions

Gold Standard:histological results
Index test:deep learning model

Sponsors

West China Hospital of Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: patients routinely scheduled for anesthetic gastroscopy

Exclusion criteria

Exclusion criteria: 1. don't agree to sign the consent. 2. have contraindications for gastroscopy or biopsy.

Design outcomes

Primary

MeasureTime frame
accuracy for detecting superficial esophageal cancer;ACC, SEN, SPE, AUC of ROC;—

Secondary

MeasureTime frame
differential diagnosis of lugol voiding lesions;—

Countries

China

Contacts

Public ContactHu Bing

West China Hospital of Sichuan University

hubingnj@163.com+86 18980601278

Outcome results

None listed

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