| Applicability Criteria |
Patients having a tumor |
| Name |
Model Card metadata |
| Based on template |
https://repo.metadatacenter.org/templates/c1252f26-9075-4934-a8ee-51695b0b892d |
| Creation date |
2023-07-19 |
| Email |
ananya.choudhury@maastro.nl |
| Out-of-scope use cases |
Analyze survival after distant metastasis of head and neck cancer |
| Description |
Model Card implementation in CEDAR forms |
| Model Input |
Computed Tomography |
| Created on |
2023-12-08T01:33:25-08:00 |
| License |
Creative Commons |
| Primary intended use |
Prove the reliability of the infrastructure to develop global models without sharing private patient data |
| Created by |
C. Zhang |
| Outcome |
Distantly Metastatic Malignant Neoplasm |
| Reference |
https://doi.org/10.21203/rs.3.rs-3158418/v |
| Primary intended users |
Researchers |
| Title |
Secure and Private Healthcare Analytics: A Feasibility Study of Federated Deep Learning with Personal Health Train |
| 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 |
2D CNNs |
| Last updated on |
2023-12-08T01:37:25-08:00 |
| http://purl.obolibrary.org/obo/IAO_0000116 |
|