Trials / Recruiting
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
- Status
- Recruiting
- Phase
- —
- Study type
- Observational
- Enrollment
- 200 (estimated)
- Sponsor
- Shanghai Pulmonary Hospital, Shanghai, China · Academic / Other
- Sex
- All
- Age
- 18 Years – 85 Years
- Healthy volunteers
- —
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.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DIAGNOSTIC_TEST | Whole Slide Image based Deep Learning | Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma |
Timeline
- Start date
- 2024-10-15
- Primary completion
- 2024-12-31
- Completion
- 2024-12-31
- First posted
- 2023-06-29
- Last updated
- 2024-10-21
Locations
3 sites across 1 country: China
Source: ClinicalTrials.gov record NCT05925764. Inclusion in this directory is not an endorsement.