Retina Age Analysis
Fundus images and age labels for retinal age prediction and regression.
At a glance
| Field | Value |
|---|---|
| Short name | retina_age_analysis |
| Full name | Retina Age Analysis |
| Primary category | fundus |
| Contained modalities | fundus |
| Tasks | regression |
| Samples | 9,857 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | 1.0 GB |
| Source-stated terms | MIT |
| Normalized terms | mit |
| Descriptive screening label | Standard label without an explicit NC clause; verify that it applies to data |
| Terms scope | unknown |
| Access friction | anonymous_direct |
| Route backend | HuggingFace Hub |
| Availability | available (checked 2026-07-21) |
| Acquisition support | standard_platform_supported |
| Legacy sample-loader status | Metadata and access only |
Notes
Provenance should be verified before clinical use.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download retina_age_analysis --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download retina_age_analysis --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('retina_age_analysis')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: huggingface.co/datasets
Source-term evidence: huggingface.co/datasets
Loader status
This catalog record provides metadata and access instructions, but it does not yet include a standard DatasetSample loader. Inspect the source file structure or contribute a loader before using it in a training pipeline.
Citation
- BibTeX
- Plain text
@misc{retina_age_analysis,
title = { Retina Age Analysis },
note = { ramankamran/retina-age-analysis. Hugging Face dataset, accessed 2026-07 },
year = { 2026 },
url = { https://huggingface.co/datasets/ramankamran/retina-age-analysis },
}
ramankamran/retina-age-analysis. Hugging Face dataset, accessed 2026-07.
Source-stated terms
- Raw source string: MIT
- Normalized category:
mit - Apparent scope:
unknown - Descriptive screening label: Standard label without an explicit NC clause; verify that it applies to data
⚠️ Source-stated terms, scope, and normalized labels are curation metadata, not legal advice or a permission finding. Review the current official source before transfer or reuse.
Related datasets with shared modalities
- airogs: AIROGS: AI for Robust Glaucoma Screening (113,893 records,
cc-by-nc-nd) - eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records,
unknown) - justraigs: JustRAIGS: Just Referral AI Glaucoma Screening Dataset (101,442 records,
cc-by-nc-nd) - eyepacs: EyePACS — Diabetic Retinopathy Detection (Kaggle 2015) (88,702 records,
research-only) - multieye: MultiEYE: OCT-Enhanced Fundus Multi-Disease Benchmark (58,036 records,
mit) - angioreport: AngioReport Fundus Angiography Report Dataset (55,361 records,
unknown) - ffa_ir: FFA-IR Medical Report Dataset (47,247 records,
unknown) - bidr: BiDR: Diabetic Retinopathy Diagnosis Dataset (35,126 records,
unknown)