RecruitingNCT05925764
WSI Based DL for Diagnosing the IASLC Grading System of Lung Adenocarcinoma
Whole Slide Image Based Deep Learning for Diagnosing the International Association for the Study of Lung Cancer Proposed Grading System of Lung Adenocarcinoma
Sponsor
Shanghai Pulmonary Hospital, Shanghai, China
Enrollment
200 participants
Start Date
Oct 15, 2024
Study Type
OBSERVATIONAL
Conditions
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.
Eligibility
Min Age: 18 YearsMax Age: 85 Years
Inclusion Criteria3
- Age ranging from 18-85 years old;
- Pathological confirmation of primary lung adenocarcinoma after surgery;
- Obtained written informed consent.
Exclusion Criteria4
- Multiple lung lesions;
- Poor quality of whole slide images;
- Mucinous adenocarcinomas and variants;
- Participants who have received neoadjuvant therapy.
Interventions
DIAGNOSTIC_TESTWhole Slide Image based Deep Learning
Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma
Locations(3)
View Full Details on ClinicalTrials.gov
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NCT05925764
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