Multimodal Al for Precision Diagnosis of Esophageal Cancer

This study intends to construct two multimodal deep learning models: one for the diagnosis of esophageal cancer and the prediction of invasive depth to assess suitability for endoscopic resection; the other model, based on this, classifies endoscopic non-resectable patients into different degrees of invasion to further explore the differences in the sensitivity and survival of AI-predicted benign and malignant tumors in patients' responses to NAT, thereby providing reliable decision support for precise individualized treatment. This aspect has rarely been addressed in previous studies.

NCT Number	NCT07629921
Lead Sponsor	Shanghai Zhongshan Hospital
Conditions	Esophageal Cancer
Enrollment	264 participants
Start Date	2023-03-01
Primary Completion	2026-01-01 (estimated)
Study Completion	2026-06-07 (estimated)
Updated on ClinicalTrials.gov	2026-08-05