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NCT05925738

Deep Learning Signature for Predicting Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer

Status unknown Last updated 29 June 2023
What this trial tests

trial testing PET/CT-based Deep Learning Signature in Non-small Cell Lung Cancer in 1,500 participants. Status unknown.

Timeline
1 May 2023
Primary endpoint
31 October 2023
31 October 2023

Quick facts

Lead sponsorShanghai Pulmonary Hospital, Shanghai, China
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment1,500
Start date1 May 2023
Primary completion31 October 2023
Estimated completion31 October 2023
Sites3 locations across China

Drugs / interventions tested

Conditions studied

Sponsor

Shanghai Pulmonary Hospital, Shanghai, China

Who can join

Adults 20 to 75, any sex, with Non-small Cell Lung Cancer or Spread Through Air Space. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting aggressive histological pattern in resected non-small cell lung cancer based on a multicenter prospective cohort.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other trials of PET/CT-based Deep Learning Signature

Trials testing the same drug.

Other recruiting trials for Non-small Cell Lung Cancer

Currently open trials in the same condition.

Other Shanghai Pulmonary Hospital, Shanghai, China trials

Trials by the same sponsor.

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Data sources for this page

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