LMOD+ Multimodal Ophthalmology Benchmark
Composite multimodal ophthalmology benchmark with multi-granular anatomical, diagnostic, staging, demographic, and text annotations.
At a glance
| Field | Value |
|---|---|
| Short name | lmod_plus |
| Full name | LMOD+ Multimodal Ophthalmology Benchmark |
| Primary category | multimodal |
| Contained modalities | fundus, oct, external_eye, surgical_video, text, tabular |
| Tasks | visual_question_answering, classification, grading, detection |
| Samples | 32,633 |
| Classes | Not reported (Not reported) |
| Splits | all |
| Size | Not reported |
| Source-stated terms | Mixed upstream licenses; verify each component |
| Normalized terms | unknown |
| Descriptive screening label | Unknown or unclear; do not assume permission |
| Terms scope | mixed_components |
| Access friction | anonymous_direct |
| Route backend | Manual (upstream-gated) |
| Availability | available (checked 2026-07-21) |
| Acquisition support | guided_instructions_only |
| Legacy sample-loader status | Metadata and access only |
Notes
Integrates 32,633 instances from nine public datasets across five modalities and 12 conditions. It adds a distinct benchmark and annotation surface but does not replace the source datasets; license and redistribution terms remain component-specific.
Access preflight and acquisition
- CLI
- Python
# Read-only preflight
eyehub download lmod_plus --data-dir ./data --dry-run --json
# Explicit transfer, only when preflight reports supported behavior
eyehub download lmod_plus --data-dir ./data
from eyedatahub.acquisition import preflight_dataset
from eyedatahub.datasets.registry import REGISTRY
ds = REGISTRY.get_dataset('lmod_plus')
print(preflight_dataset(ds, './data')) # no transfer
Upstream page: kfzyqin.github.io/lmod_plus
Source-term evidence: kfzyqin.github.io/lmod_plus
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{lmod_plus,
title = { LMOD+ Multimodal Ophthalmology Benchmark },
note = { Qin Z, Liu Y, Yin Y, et al. LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology. ACM Transactions on Computing for Healthcare. 2026. doi:10.1145/3801746 },
year = { 2026 },
url = { https://kfzyqin.github.io/lmod_plus/ },
}
Qin Z, Liu Y, Yin Y, et al. LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology. ACM Transactions on Computing for Healthcare. 2026. doi:10.1145/3801746
Source-stated terms
- Raw source string: Mixed upstream licenses; verify each component
- Normalized category:
unknown - Apparent scope:
mixed_components - Descriptive screening label: Unknown or unclear; do not assume permission
⚠️ 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
- eyecare_100k: Eyecare-100K: Multimodal Ophthalmology VQA Corpus (102,000 records,
unknown) - x_pcr: X-PCR Ophthalmology Progressive Clinical Reasoning Benchmark (18,700 records,
unknown) - ophthalvqa: OphthalVQA Dataset (count not reported records,
cc-by) - olives: OLIVES: Ophthalmic Labels for Investigating Visual Eye Semantics (9,408 records,
cc-by) - grape: GRAPE: Glaucoma Real-world Appraisal Progression Ensemble (1,115 records,
cc0) - dryad_subretinal_robot: Head-Mounted Robot Subretinal Injection Dataset (count not reported records,
cc0) - fairvlmed: FairVLMed: Fair Vision-Language Medical Ophthalmic Dataset (count not reported records,
unknown) - mm_retinal_reason: MM-Retinal-Reason: Ophthalmology Multimodal Reasoning Dataset (count not reported records,
unknown)