| --- |
| license: mit |
| tags: |
| - text-classification |
| - eye-imaging |
| - ophthalmology |
| - medical-imaging |
| - fair-data |
| - eyeact |
| --- |
| |
| # ENVISION Eye Imaging Training Data |
|
|
| Training dataset for the [ENVISION eye imaging classifier](https://huggingface.co/fairdataihub/envision-eye-imaging-classifier). |
|
|
| ## Dataset Description |
|
|
| 994 curated text examples for binary classification of eye imaging datasets from scientific metadata. |
|
|
| | Label | Count | Description | |
| |-------|-------|-------------| |
| | EYE_IMAGING | 365 | Ophthalmic imaging datasets (fundus, OCT, OCTA, cornea) | |
| | NEGATIVE | 629 | Non-imaging data (software, other eye research, unrelated) | |
| |
| ### Source Composition |
| |
| **EYE_IMAGING (365)**: |
| - 77 hand-curated examples from multi-repository sources |
| - 288 expert-verified positives from cross-repository classification |
| |
| **NEGATIVE (629)**: |
| - 502 general negative examples |
| - 48 eye-related software examples (hard negatives) |
| - 79 non-imaging eye data examples (hard negatives) |
| |
| ### Data Format |
| |
| Each example is a text string representing concatenated metadata fields (title, description, keywords, file types) from scientific data repositories (Zenodo, Figshare, Dryad, Kaggle, NEI). |
| |
| ## Usage |
| |
| ```python |
| from datasets import load_dataset |
|
|
| ds = load_dataset("fairdataihub/envision-eye-imaging-training-data") |
| ``` |
| |
| ## Citation |
| |
| - EyeACT Envision project |
| - FAIR Data Innovations Hub (fairdataihub.org) |
| |
