CLINICAL_TRIALS ClinicalTrials.gov record update

Integration of Clinical, Radiomics, and 2.5D Deep Learning-Based Multiple Instance Learning Features for Predicting Pathological Complete Response in Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunotherapy and Chemotherapy: A Multicenter Comparative Study

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Record identity and dates

Source: ClinicalTrials.gov
Source record ID: NCT07181850
Title field or adapter rule: protocolSection.identificationModule.officialTitle
Ingested At: 2026-04-25T22:27:18.139019+00:00
Published At: 2025-09-18T00:00:00+00:00
Record Updated At: 2025-09-18
Timestamp Basis: source retrieval time was not retained by the feed adapter
Date limitation: source retrieval time was not retained by the feed adapter

protocolSection.conditionsModule.conditions: ["Esophageal Squamous Cell Carcinoma", "Pathological Complete Response"]
protocolSection.statusModule.lastUpdatePostDateStruct.date: "2025-09-18"
protocolSection.identificationModule.nctId: "NCT07181850"
protocolSection.identificationModule.officialTitle: "Integration of Clinical, Radiomics, and 2.5D Deep Learning-Based Multiple Instance Learning Features for Predicting Pathological Complete Response in Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunotherapy and Chemotherapy: A Multicenter Comparative Study"
protocolSection.statusModule.overallStatus: "COMPLETED"
protocolSection.designModule.phases: []
protocolSection.statusModule.resultsFirstPostDateStruct.date: ""

Intervention details are not present in the imported fields for this record. No drug-condition relationship is inferred from co-listing.

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