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NCT07203690

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

Not yet recruiting Last updated 2 October 2025
What this trial tests

trial in Esophageal Cancer in 7,000 participants. Not yet recruiting.

Timeline
1 December 2025
Primary endpoint
31 January 2027
1 December 2027

Quick facts

Lead sponsorHenan Cancer Hospital
StatusNot yet recruiting
Study typeOBSERVATIONAL
Enrollment7,000
Start date1 December 2025
Primary completion31 January 2027
Estimated completion1 December 2027

Conditions studied

Sponsor

Henan Cancer Hospital

Who can join

18 and older, any sex, with Esophageal Cancer or Neoadjuvant Therapy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Esophageal Cancer

Currently open trials in the same condition.

Other Henan Cancer Hospital trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07203690.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing