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FIDELIS
Zx93/FIDELIS
FIDELIS is a machine learning model from Zx93. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Model artifacts for FIDELIS, an open-source tool that evaluates the calibration and robustness of trained deep-learning models in cancer imaging. FIDELIS operates post-hoc on a model's outputs — no retraining, no acce…
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Updated Jul 8, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026
- SHA
- 3eed68ba
Model card
From the Hugging Face model README
FIDELIS — Reliability Estimators
Model artifacts for FIDELIS, an open-source tool that evaluates the calibration and robustness of trained deep-learning models in cancer imaging. FIDELIS operates post-hoc on a model's outputs — no retraining, no access to the original training data — and returns a clinician-facing reliability report.
- Code: https://github.com/ZhixiangWang-CN/FIDELIS
- Program: NCI ITCR (RFA-CA-27-019, U01)
Components (to be released)
- FIDELIS-Calibrate — post-hoc calibration assessment (Anatomy-Aware ECE / ΔA-ECE) and recalibration maps.
- FIDELIS-Robust — stability under simulated scanner / dose / protocol variation.
- Clinical Decision Impact (CDI) — maps reliability failures to potential changes in a clinical decision.
Status
Repository reserved during early development; trained components and full model cards will be uploaded and version-tagged with each release. Not a diagnostic device; not for autonomous clinical decision-making.
License
Code components: Apache-2.0. Standalone model weights: CC-BY-4.0.
- License
- apache-2.0
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026