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Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer （Radiogenomics-Esophagus）

Recruitingn/aAges any - anyAllShu Peng
NCT07354295 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

This AI-driven model leverages multimodal data-such as radiomics, pathomics, genomics, and broader multi-omics profiles-to capture complementary aspects of tumor biology and predict treatment response and prognosis.

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📋 Eligibility rules (as published)
Inclusion Criteria: 1. Histopathologically diagnosed esophageal cancer 2. Complete baseline clinical data available (including demographic characteristics, ECOG performance score, TNM staging, etc.) 3. No other primary malignant tumors 4. Provision of informed consent 5. Availability of pre-treatment CT imaging Exclusion Criteria: 1. Imaging data quality insufficient for analysis 2. Presence of another primary malignant tumor 3. Severe systemic disease
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What it tests

  • Not listed
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Where

1 site
Tongji hospital, Tongji medical college, Huazhong university of science and technology
Wuhan, China
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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