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RECRUITING
NCT05925764

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

Sponsor: Shanghai Pulmonary Hospital, Shanghai, China

View on ClinicalTrials.gov

Summary

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.

Official title: Whole Slide Image Based Deep Learning for Diagnosing the International Association for the Study of Lung Cancer Proposed Grading System of Lung Adenocarcinoma

Key Details

Gender

All

Age Range

18 Years - 85 Years

Study Type

OBSERVATIONAL

Enrollment

200

Start Date

2024-10-15

Completion Date

2024-12-31

Last Updated

2024-10-21

Healthy Volunteers

Not specified

Interventions

DIAGNOSTIC_TEST

Whole Slide Image based Deep Learning

Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

Locations (3)

Affiliated Hospital of Zunyi Medical University

Zunyi, Guizhou, China

The First Affiliated Hospital of Nanchang University

Nanchang, Jiangxi, China

Ningbo HwaMei Hospital

Ningbo, Zhejiang, China