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A diagnostic test of an artificial intelligence-aided diagnosis system for endoscopic ultrasonography

A prospective study for the effectiveness of artificial intelligence assisted diagnosis system in the diagnosis of gastrointestinal subepithelial lesions lesions

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100050434
Enrollment
Unknown
Registered
2021-08-27
Start date
2021-08-20
Completion date
Unknown
Last updated
2022-05-02

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

Conditions

Gastrointestinal subepithelial lesions

Interventions

Gold Standard:Pathological diagnosis
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Sponsors

The Affiliated Hospital of Qingdao University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients with submucosal lesions diagnosed by ordinary white light endoscopy. 2. Before deciding to perform endoscopic ultrasonography, the patients were introduced to this study, and the patients were enrolled after signing the informed consent.

Exclusion criteria

Exclusion criteria: 1. Patients with submucosal lesions diagnosed during white light endoscopy and confirmed as abdominal organ compression and blood vessels under endoscopic ultrasonography. 2. Patients who signed informed consent but failed to undergo qualified endoscopic ultrasonography for various reasons.

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy;Macro-F1 score;

Countries

China

Contacts

Public ContactLi Xiaoyu

The Affiliated Hospital of Qingdao University

lixiaoyu0@163.com+86 17853299211

Outcome results

None listed

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