Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer

Summary

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.

Eligibility

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

Conditions2

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