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Multicenter Observational Study of Multimodal AI for Upper GI Mesenchymal Tumor Diagnosis

NCT07078136 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 130

Last updated 2025-07-31

No results posted yet for this study

Summary

This study develops a multimodal AI model using endoscopic ultrasound, white-light endoscopy, and clinical information to support the diagnosis of upper GI mesenchymal tumors and the risk stratification of gastric GISTs.

Conditions

  • Submucosal Tumor
  • Gastrointestinal Stromal Tumor (GIST)
  • Leiomyoma
  • Schwannoma

Interventions

DIAGNOSTIC_TEST

Multimodal AI Model

Patients' endoscopic images, EUS images, and clinical data will be analyzed by a multimodal AI model for lesion classification and GIST risk stratification.

DIAGNOSTIC_TEST

Expert Endoscopist Assessment

Endoscopic ultrasound images will be interpreted by experienced endoscopists for comparison with the AI model.

Sponsors & Collaborators

  • Huazhong University of Science and Technology

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-28
Primary Completion
2026-03-31
Completion
2026-06-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07078136 on ClinicalTrials.gov