Multicenter Observational Study of Multimodal AI for Upper GI Mesenchymal Tumor Diagnosis
Multicenter Observational Study of a Multimodal AI Model Using EUS, White-Light Endoscopy, and Clinical Data for Diagnosis of Upper GI Mesenchymal Tumors and Risk Stratification of Gastric GISTs
Huazhong University of Science and Technology
130 participants
Jul 28, 2025
OBSERVATIONAL
Conditions
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.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
Patients' endoscopic images, EUS images, and clinical data will be analyzed by a multimodal AI model for lesion classification and GIST risk stratification.
Endoscopic ultrasound images will be interpreted by experienced endoscopists for comparison with the AI model.
Locations(1)
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NCT07078136