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Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer

NCT05925751 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2023-06-29

No results posted yet for this study

Summary

The purpose of this study is to evaluate the performance of a CT/PET/ WSI-based deep learning signature for predicting complete pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer

Conditions

Interventions

DIAGNOSTIC_TEST

CT/PET/WSI-based Deep Learning Signature

CT/PET/WSI-based Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer

Sponsors & Collaborators

  • Ningbo No.2 Hospital

    collaborator OTHER

  • Zunyi Medical College

    collaborator OTHER

  • The First Affiliated Hospital of Nanchang University

    collaborator OTHER

  • Shanghai Pulmonary Hospital, Shanghai, China

    lead OTHER

Eligibility

Min Age
20 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-05-01
Primary Completion
2023-10-31
Completion
2023-10-31

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 NCT05925751 on ClinicalTrials.gov