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AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases

NCT07087418 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 5000

Last updated 2026-04-13

No results posted yet for this study

Summary

The goal of this observational, retrospective and prospective study is to develop a noninvasive disease assessment system by leveraging artificial intelligence (AI) to comprehensively analyze multi-modal imaging features, including magnetic resonance enterography (MRE) and computed tomography enterography (CTE), for the diagnosis and prognostication of digestive diseases. To this end, the investigators retrospectively enrolled imaging, endoscopic, and clinical data from 21 centers across China to construct and iteratively optimize the AI model. The model's performance will be prospectively validated in two centers, and its accuracy in lesion localization will be verified through real-world deployment in endoscopy suites.

Conditions

  • Digestive Diseases
  • Radiology
  • AI (Artificial Intelligence)
  • Imaging

Interventions

DIAGNOSTIC_TEST

Virtual endoscopy model-assisted diagnosis

Using the virtual endoscopy model to aid diagnosis

Sponsors & Collaborators

  • First Affiliated Hospital, Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • Xuehua Li · Sun Yat-sen University First Affiliated Hospital Department of Radiology

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-07-01
Primary Completion
2026-08-01
Completion
2026-08-01

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 NCT07087418 on ClinicalTrials.gov