MedTrace Logo

Deep Learning Model to Predict the Recurrence of Stage IA Invasive Lung Adenocarcinoma After Sub-lobar Resection

NCT06659601 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 9

Last updated 2024-10-26

No results posted yet for this study

Summary

This study aims to develop a deep learning model based on noncontrast CT images to predict the recurrence risk of stage IA invasive lung adenocarcinoma after sub-lobar resection，which can serve as potential tool to assist thoracic surgeons in making optimal treatment decisions.The study will use existing CT data to train and validate the model, without requiring any additional intervention for the participants.

Conditions

  • Focus on Developing a Deep Learning Model to Predict the Recurrence Risk of Stage IA Invasive Lung Adenocarcinoma After Sub-lobar Resection

Sponsors & Collaborators

  • First Affiliated Hospital of Chongqing Medical University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-06-01
Primary Completion
2024-01-01
Completion
2024-10-24

Countries

  • China

More Related Trials

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 NCT06659601 on ClinicalTrials.gov