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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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Whole Slide Image based Deep Learning | Diagnostic Test | Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma |
| Measure | Description | Time Frame |
|---|---|---|
| Agreement rate of the IASLC grading system | Agreement rate between the deep learning model and pathologists in diagnosing the IASLC grade of lung adenocarcinoma. | 2024.11.01-2024.12.31 |
| Measure | Description | Time Frame |
|---|---|---|
| Agreement rate of the predominant subtypes | Agreement rate between the deep learning model and pathologists in diagnosing the predominant growth patterns of lung adenocarcinoma. | 2024.11.01-2024.12.31 |
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Inclusion Criteria:
Exclusion Criteria:
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Resected Lung Adenocarcinoma
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Affiliated Hospital of Zunyi Medical University | Recruiting | Zunyi | Guizhou | China |
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| ID | Term |
|---|---|
| D000077192 | Adenocarcinoma of Lung |
| ID | Term |
|---|---|
| D000230 | Adenocarcinoma |
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
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| The First Affiliated Hospital of Nanchang University | Recruiting | Nanchang | Jiangxi | China |
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| Ningbo HwaMei Hospital | Recruiting | Ningbo | Zhejiang | China |
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| D009369 | Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |