ncbi/OcularChat-VQA

---
license: cc-by-nc-sa-4.0
---
# OcularChat Dataset

To ensure clinical relevance and contextual accuracy during model training, simulated patient-physician dialogues were generated using key clinical variables extracted from the AREDS dataset. These variables included demographic characteristics (age, gender, diabetes status, and smoking history) and ophthalmic features (presence of advanced AMD, maximum drusen size, and presence of pigmentary abnormalities).

# Datasets
You can first download the [AREDS dataset](https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000001.v3.p1). Split it into train, valid, test subsets.

To generate your own patient-physician dialogues, please run:
```
python genterate_areds.py
```

We also share our generated dialogues for your convenient research-only purpose.

# Disclaimer
This tool shows the results of research conducted in the Computational Biology Branch, DIR/NLM. The information produced on this website is not intended for direct diagnostic use or medical decision-making without review and oversight by a clinical professional. Individuals should not change their health behavior solely on the basis of information produced on this website. NIH does not independently verify the validity or utility of the information produced by this tool. If you have questions about the information produced on this website, please see a health care professional. More information about NLM's disclaimer policy is available at https://www.nlm.nih.gov/web_policies.html.

# Acknowledgement
This research was supported by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.

# Citation
If you find our work helpful, pleaes cite it by:
```bibtex
@article{gu2026ocularchat,
title={Toward Multimodal Conversational AI for Age-Related Macular Degeneration},
author={Ran Gu, Benjamin Hou, Mélanie Hébert, Asmita Indurkar, Yifan Yang, Emily Y. Chew, Tiarnán D. L. Keenan, Zhiyong Lu},
year={2026}
}
```