Datasets:
language:
- en
pretty_name: PubMedVision-Plus
task_categories:
- image-to-text
tags:
- medical
- biomedical
- multimodal
- image-captioning
- pubmed
- huatuogpt
configs:
- config_name: core
data_files:
- split: train
path: core-*.parquet
- config_name: sample
default: true
data_files:
- split: train
path: sample/sample.parquet
⚡ Introduction
PubMedVision-Plus is a large-scale medical image–text dataset built from scientific literature, pairing original figures with expert-authored captions to support medical multimodal pretraining.
- Medical knowledge at scale. Drawing on approximately 15M PubMed papers, the collection is refined through LLM- and VLM-based quality filtering into a 12M high-quality Core.
- Broad visual coverage. From radiology and pathology to microscopy, ophthalmology, and endoscopy, the data span diverse medical specialties, with modality and anatomical-region labels retained in the browsing sample.
License notice: Images and captions come from medical journal articles. Please follow the source journals’ image-use and attribution requirements. See the PMC reuse guidelines.
📚 Data
Each Core record includes a unique ID, a relative image path, and its corresponding caption. The browsing sample additionally retains modality and anatomical-region labels and embeds the images.
| Data | Image–caption pairs | Construction |
|---|---|---|
| Core | 12,444,904 | Medical literature collection, followed by LLM/VLM quality filtering. |
Original figures and author-written captions are preserved without generative rewriting, avoiding hallucinations introduced by synthetic captions. Filtering targets defective images and problematic image–text pairs.
🚀 Usage
PubMedVision-Plus/
├── README.md
├── core-*.parquet # IDs, captions, and relative image paths
├── images/images-*.tar # Original image archives
└── sample/sample.parquet # Examples with embedded images
The Core collection contains 12,444,904 pairs. The browsing sample currently contains 50 examples.
Load the image-embedded sample Parquet from the downloaded repository:
from datasets import load_dataset
dataset = load_dataset("parquet", data_files="sample/sample.parquet", split="train")
image, caption = dataset[0]["image"], dataset[0]["caption"]
For the full Core release, extract all image tar shards from the repository root (four archives in parallel):
find images -maxdepth 1 -type f -name '*.tar' -print0 \
| xargs -0 -P 4 -I {} tar -xf '{}' -C .
Extraction preserves the relative image paths in the Parquet metadata. Load core-*.parquet to access IDs, captions, and the corresponding image paths.
📄 Related work
PubMedVision-Plus is introduced in Incentivizing Medical Vision Capabilities from Large-Scale Multimodal Pre-training (NeurIPS 2026). If you use this dataset, please cite:
@inproceedings{chen2026incentivizing,
title={Incentivizing Medical Vision Capabilities from Large-Scale Multimodal Pre-training},
author={Chen, Junying and Cai, Zhenyang and Yang, Yunjin and Cai, Kunyuan and Wang, Rongsheng and Wang, Xidong and Yu, Geyang and Feng, Xiangyi and Wang, Benyou},
booktitle={The Fortieth Annual Conference on Neural Information Processing Systems},
year={2026}
}