Development and Application of AI-Based Therapeutic Strategies for Esophageal Cancer Integrating Multimodal Imaging and Digital Pathology

Brief summary (registry, in English)

The purpose of this clinical study is to conduct a multi-center, big data study to create a neural network decision model for predicting treatment efficacy and prognosis based on multi-modal, multi-temporal imaging features combined with tumor microenvironment scores. It will also use various model interpretation techniques to clarify the role and mechanism of key biomarkers or strongly associated biomarker groups in treatment efficacy and prognosis. Ultimately, it aims to achieve the research and application of AI treatment strategies combining multi-modal imaging and digital pathology to guide clinicians in the personalized treatment strategies for patients with esophageal squamous cell carcinoma.

What you commit to

• Study type: Observational
• Planned participants: 7000
• From 1 Dec 2025 to the primary completion date, 31 Jan 2027
• No sites listed in no country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Age in the registry: 18 years to - · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov