Trials / Unknown
UnknownNCT05925751
Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer
An Integration of a Computed Tomography/Positron Emission Tomography/Whole Slide Image (CT/PET/WSI) Based Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer: A Multicenter Study
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 100 (estimated)
- Sponsor
- Shanghai Pulmonary Hospital, Shanghai, China · Academic / Other
- Sex
- All
- Age
- 20 Years – 75 Years
- Healthy volunteers
- —
Summary
The purpose of this study is to evaluate the performance of a CT/PET/ WSI-based deep learning signature for predicting complete pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DIAGNOSTIC_TEST | CT/PET/WSI-based Deep Learning Signature | CT/PET/WSI-based Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer |
Timeline
- Start date
- 2023-05-01
- Primary completion
- 2023-10-31
- Completion
- 2023-10-31
- First posted
- 2023-06-29
- Last updated
- 2023-06-29
Locations
3 sites across 1 country: China
Source: ClinicalTrials.gov record NCT05925751. Inclusion in this directory is not an endorsement.