Harvard GDP: Glaucoma Detection and Progression Dataset

1,000 patients with OCT RNFLT maps (225×225), visual field measurements, and demographics for glaucoma detection (binary) and longitudinal progression forecasting (6 definitions). First public glaucoma progression dataset from Harvard Ophthalmology AI Lab.

At a glance

Field	Value
Short name	harvard_gdp
Full name	Harvard GDP: Glaucoma Detection and Progression Dataset
First published	Unknown
Publication date precision	Unknown
Publication date evidence	Unknown
Publication date source field	Unknown
Publication date reviewed	Unknown
Primary category	oct
Resource role	current_dataset
Dataset family	harvard_gdp
Contained modalities	oct, visual_field, tabular
Tasks	classification, progression
Primary reported quantity	1,000 participants
Classes	2 (Non-Glaucoma, Glaucoma)
Splits	train, val, test
Size	2.0 GB
Source-stated terms	CC BY-NC-ND 4.0
Normalized terms	cc-by-nc-nd
Descriptive screening label	Explicit noncommercial clause recorded; check source
Terms scope	dataset_files
Access friction	anonymous_direct
Route backend	Google Drive
Availability	available (checked 2026-07-21)
Acquisition support	guided_instructions_only
Legacy sample-loader status	Standard loader included

Reported quantities

Role	Count	Unit	Scope	Basis	Evidence
Primary	1,000	participants	Primary quantity reported in the reviewed catalog source	legacy_catalog_field	drive.google.com/drive

Counts retain their source-reported units. Additional rows can describe components, paired items, or derivative copies and are not automatically added to the primary quantity.

Documented relationships

These links record source-supported lineage or overlap, not merely similar modality tags.

• x_pcr is derived from this record: Source labels in the version-pinned public X-PCR deposit identify this catalog record as upstream material. (evidence)

Access information and download

CLI

# Read-only preflight
eyehub download harvard_gdp --data-dir ./data --dry-run --json

# Download, only when preflight reports supported behavior
eyehub download harvard_gdp --data-dir ./data

Python

from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY

ds = REGISTRY.get_dataset('harvard_gdp')
print(preflight_dataset(ds, './data'))  # no download

Upstream page: drive.google.com/drive

Source-term evidence: drive.google.com/drive

Loader example

This entry includes a standard DatasetSample loader.

from pathlib import Path
from eyedatahub.datasets.registry import REGISTRY

data_dir = Path('~/.eyedatahub/data').expanduser()
ds = REGISTRY.get_dataset('harvard_gdp')
samples = ds.load(data_dir, split='test')
for s in samples[:5]:
    print(s.sample_id, s.label, s.image_path)

Citation

BibTeX

@misc{harvard_gdp,
  title  = { Harvard GDP: Glaucoma Detection and Progression Dataset },
  note   = { Luo Z et al., 'Glaucoma Progression Prediction Using Retinal Thickness via Deep Learning', arXiv 2308.13411, 2023. https://github.com/Harvard-Ophthalmology-AI-Lab/Harvard-GDP },
  year   = { 2023 },
  url    = { https://drive.google.com/drive/folders/1JMi_HCql113uc9X0DOaMkNfEWfxaDlEz },
}

Plain text

Luo Z et al., 'Glaucoma Progression Prediction Using Retinal Thickness via Deep Learning', arXiv 2308.13411, 2023. https://github.com/Harvard-Ophthalmology-AI-Lab/Harvard-GDP

Source-stated terms

• Raw source string: CC BY-NC-ND 4.0
• Normalized category: cc-by-nc-nd
• Apparent scope: dataset_files
• Descriptive screening label: Explicit noncommercial clause recorded; check source

⚠️ 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.

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