| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - image-classification |
| - explainable-ai |
| - medical-imaging |
| - grad-cam |
| --- |
| |
| # T1 MLOps Stack — ChestXplain Checkpoint |
|
|
| This repository contains the approved DenseNet121 checkpoint used by the ChestXplain research/demo application. The application performs multi-label classification of 14 thoracic conditions and provides Grad-CAM visual explanations. |
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| ## Training provenance |
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| - **Architecture:** DenseNet121 with a multi-label classification head |
| - **Dataset:** NIH ChestX-ray14-derived training subset |
| - **Training subset:** 20,000 images |
| - **Checkpoint epoch:** 6 |
| - **Validation AUC:** 0.813 (recorded in the checkpoint metadata) |
| - **Checkpoint SHA-256:** `5bf5e15396805ac85a5c1f1839813bc4ea3a66ff694f5ed6f12c1fd2eaee0cbf` |
| - **Artifact:** `densenet121_chestxray.pth` |
|
|
| The checkpoint is provided as a model artifact for the associated portfolio MLOps demonstration. NIH images and source data are not included in this repository. |
|
|
| ## Intended use |
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| Research, engineering evaluation, and educational/demo use only. This artifact is not validated for clinical deployment and must not be used to diagnose, treat, or make decisions about patients. |
|
|
| ## Limitations |
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| - The model was trained on a 20,000-image subset rather than the complete NIH ChestX-ray14 dataset. |
| - Dataset labels are noisy and may not represent definitive clinical diagnoses. |
| - Performance may vary across institutions, scanners, patient populations, acquisition protocols, and disease prevalence. |
| - Reported metrics are not evidence of clinical efficacy, safety, fairness, or regulatory approval. |
| - Grad-CAM highlights model attribution regions; it is not a clinical explanation or proof of pathology. |
| - The checkpoint has not undergone external validation, prospective evaluation, calibration analysis, or regulatory review. |
|
|
| ## License and provenance |
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| The model artifact is released under the repository's MIT license for research/demo purposes, subject to the terms and attribution requirements of the underlying NIH ChestX-ray14 dataset and its original publication. See the associated source project for inference code, evaluation context, and full citations: |
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|
| <https://github.com/ajinkya-awari/t1-mlops-stack> |
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