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NCT05925764

WSI Based DL for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

Recruiting now Last updated 21 October 2024
What this trial tests

trial testing Whole Slide Image based Deep Learning in Lung Adenocarcinoma in 200 participants. Currently enrolling.

Timeline
15 October 2024
Primary endpoint
31 December 2024
31 December 2024

Quick facts

Lead sponsorShanghai Pulmonary Hospital, Shanghai, China
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment200
Start date15 October 2024
Primary completion31 December 2024
Estimated completion31 December 2024
Sites3 locations across China

Drugs / interventions tested

Conditions studied

Sponsor

Shanghai Pulmonary Hospital, Shanghai, China

Who can join

Adults 18 to 85, any sex, with Lung Adenocarcinoma or Whole Slide Image. 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 whole slide image based deep learning model for diagnosing the IASLC grading system in resected lung adenocarcinoma based on a multicenter prospective cohort.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. Systematic scoping review of external validation studies of AI pathology models for lung cancer diagnosis.
    Arun S, Grosheva M, Kosenko M, Robertus JL, et al · · 2025 · cited 6× · PMID 40483288 · DOI 10.1038/s41698-025-00940-7

Verify or expand the search:

Other recruiting trials for Lung Adenocarcinoma

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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