| Applicability Criteria |
Treated with a combination of surgery, chemotherapy, and radiotherapy |
| Applicability Criteria |
Patients diagnosed with non-small cell lung cancer |
| Applicability Criteria |
Patients with available CT images |
| Name |
External Validation of Robust Radiomic Signature to Predict 2‐Year Overall Survival in Non‐Small‐Cell Lung Cancer |
| Based on template |
https://repo.metadatacenter.org/templates/c1252f26-9075-4934-a8ee-51695b0b892d |
| Creation date |
2023-09-21 |
| Email |
a.jha@maastrichtuniversity.nl |
| Ethical considerations - risks and harms |
Predicted outcome should not be used as the sole decision for treatment |
| Out-of-scope use cases |
Automated decision making |
| Description |
Model Card implementation in CEDAR forms |
| Model Input |
Gross Tumor Volume |
| Model Input |
RTStructureSet |
| Model Input |
DICOM-RT |
| Model Input |
Computed Tomography |
| Created on |
2023-11-30T08:04:13-08:00 |
| License |
Creative Commons |
| Primary intended use |
Patients diagnosed with non-small cell lung cancer |
| Primary intended use |
Prediction of 2-year overall survival |
| Created by |
Ashish Kumar Jha |
| Ethical considerations - Human life |
Intended to support decisions regarding treatment options |
| Outcome |
Less Than Two Years Survival |
| Reference |
https://doi.org/10.1007/s10278-023-00835-8 |
| Primary intended users |
Clinicians |
| Title |
External Validation of Robust Radiomic Signature to Predict 2‐Year Overall Survival in Non‐Small‐Cell Lung Cancer |
| Created by |
https://metadatacenter.org/users/0428302b-d7f9-45ff-a4ff-a27f62df6fb6 |
| Modified by |
https://metadatacenter.org/users/0428302b-d7f9-45ff-a4ff-a27f62df6fb6 |
| Foundational model or algorithm used |
Random Forest (RFC), Support Vector (SVC), and Gradient Boosting Classifier (GBC) |
| Last updated on |
2023-12-07T04:35:33-08:00 |
| Ethical considerations - Mitigations |
Data requests were approved by local institutional review board |
| Ethical considerations - Data |
Model input contains information about a patient's condition |