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Development and Validation of a Deep Learning-Based Survival Prediction Model for Pediatric Glioma Patients: A Retrospective Study Using the SEER Database and Chinese Data

NCT06199388 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 9532

Last updated 2024-01-10

No results posted yet for this study

Summary

Accurately predicting the survival of pediatric glioma patients is crucial for informed clinical decision-making and selecting appropriate treatment strategies. However, there is a lack of prognostic models specifically tailored for pediatric glioma patients. This study aimed to address this gap by developing a time-dependent deep learning model to aid physicians in making more accurate prognostic assessments and treatment decisions.

Conditions

Interventions

OTHER

Survival state

We recorded clinically relevant information and survival status of pediatric glioma patients

Sponsors & Collaborators

  • Tang-Du Hospital

    lead OTHER

Eligibility

Max Age
21 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-09-20
Primary Completion
2023-08-16
Completion
2023-12-20

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

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 NCT06199388 on ClinicalTrials.gov