rajpurkarlab/ReXInTheWild

---
pretty_name: ReXInTheWild
license: cc-by-nc-nd-3.0
task_categories:
- visual-question-answering
- question-answering
configs:
- config_name: default
data_files:
- split: eval
path: data/qa.csv
---

# ReXInTheWild: A Unified Benchmark for Medical Photograph Understanding

## Overview
ReXInTheWild is an expert-verified VQA benchmark for evaluating vision–language models on **medical photographs taken with ordinary cameras**. Unlike traditional medical VQA datasets focused on specialized imaging (e.g., X-rays, pathology), this dataset targets **everyday photographs containing medically relevant content**, requiring both natural image understanding and clinical reasoning.

The dataset contains 955 clinician-verified multiple-choice questions about 484 images. Images were selected from the Biomedica dataset, a collection of PubMed Central images.

If you use this dataset, please cite the associated paper: *ReXInTheWild: A Unified Benchmark for Medical Photograph Understanding*.

## Dataset Structure
- `data/qa.csv`: question-answer pairs and metadata
- `data/images/`: corresponding images

Each row includes:
- `file_name`: relative path to image
- `question`
- `choice_a`–`choice_e` (3-5 answers per question)
- `answer`
- `tag`: clinical category (Head & Neck, Trunk & Extremities, etc.)
- article metadata (title, authors, link)

## Licensing
This dataset is released under **CC BY-NC-ND 3.0**.

Images are derived from the noncommercial split of the PubMed Central Open Access Subset and carry individual license restrictions (CC-BY-NC, CC-BY-NC-SA, or CC-BY-NC-ND). We release the dataset under CC-BY-NC-ND, the most restrictive license.

## Bibliography
Lozano, A., Sun, M.W., et al.: BIOMEDICA: An open biomedical image-caption archive, dataset, and vision-language models derived from scientific literature (2025)