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

NCT07354295 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2026-03-10

No results posted yet for this study

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.

Conditions

  • Esophageal Cancer

Sponsors & Collaborators

  • Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

    collaborator OTHER

  • The First Affiliated Hospital of Henan University of Science and Technology

    collaborator OTHER

  • Henan Provincial People's Hospital

    collaborator OTHER

  • Zhongnan Hospital

    collaborator OTHER

  • Renmin Hospital of Wuhan University

    collaborator OTHER

  • Shu Peng

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-26
Primary Completion
2030-09-30
Completion
2030-09-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07354295 on ClinicalTrials.gov