CLINICAL_TRIALS ClinicalTrials.gov record update

Machine Learning Model to Predict Hospital Length of Stay (HOLS) and Mortality After Discharge in Hospitalized Oncologic Patients [Plantology Database]: a Multicenter Cross-validation Study

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Record identity and dates

Source: ClinicalTrials.gov
Source record ID: NCT05534178
Title field or adapter rule: protocolSection.identificationModule.officialTitle
Ingested At: 2026-04-28T10:38:59.723755+00:00
Published At: 2022-09-09T00:00:00+00:00
Record Updated At: 2022-09-09
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: ["Solid Tumor", "Nutrition Related Neoplasm/Cancer", "Comorbidities and Coexisting Conditions", "Mental Status Change", "Artificial Intelligence", "Oncology", "Tumor", "Quality of Life"]
protocolSection.statusModule.lastUpdatePostDateStruct.date: "2022-09-09"
protocolSection.identificationModule.nctId: "NCT05534178"
protocolSection.identificationModule.officialTitle: "Machine Learning Model to Predict Hospital Length of Stay (HOLS) and Mortality After Discharge in Hospitalized Oncologic Patients [Plantology Database]: a Multicenter Cross-validation Study"
protocolSection.statusModule.overallStatus: "UNKNOWN"
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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