Create README.md

README.md

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+---
+task_categories:
+- question-answering
+language:
+- en
+- he
+- ja
+- es
+- pt
+tags:
+- medical
+size_categories:
+- n<1K
+---
+
+# WorldMedQA-V: A Multilingual, Multimodal Medical Examination Dataset
+
+## Overview
+
+**WorldMedQA-V** is a multilingual and multimodal benchmarking dataset designed to evaluate vision-language models (VLMs) in healthcare contexts. The dataset includes medical examination questions from four countries—Brazil, Israel, Japan, and Spain—in both their original languages and English translations. Each multiple-choice question is paired with a corresponding medical image, enabling the evaluation of VLMs on multimodal data.
+
+**Key Features:**
+- **Multilingual:** Supports local languages (Portuguese, Hebrew, Japanese, and Spanish) as well as English translations.
+- **Multimodal:** Each question is accompanied by a medical image, allowing for a comprehensive assessment of VLMs' performance on both textual and visual inputs.
+- **Clinically Validated:** All questions and answers have been reviewed and validated by native-speaking clinicians from the respective countries.
+
+## Dataset Details
+
+- **Number of Questions:** 568
+- **Countries Covered:** Brazil, Israel, Japan, Spain
+- **Languages:** Portuguese, Hebrew, Japanese, Spanish, and English
+- **Types of Data:** Multiple-choice questions with medical images
+- **Evaluation:** Performance of models in both local languages and English, with and without medical images
+
+The dataset aims to bridge the gap between real-world healthcare settings and AI evaluations, fostering more equitable, effective, and representative applications.
+
+## Data Structure
+
+The dataset is provided in TSV format, with the following structure:
+- **ID**: Unique identifier for each question.
+- **Question**: The medical multiple-choice question in the local language.
+- **Options**: List of possible answers (A-D).
+- **Correct Answer**: The correct answer's label.
+- **Image Path**: Path to the corresponding medical image (if applicable).
+- **Language**: The language of the question (original or English translation).
+
+### Example from Brazil:
+
+- **Question**: Um paciente do sexo masculino, 55 anos de idade, tabagista 60 maços/ano... [Full medical question]
+- **Options**:
+  - A: Aspergilose pulmonar
+  - B: Carcinoma pulmonar
+  - C: Tuberculose cavitária
+  - D: Bronquiectasia com infecção
+- **Correct Answer**: B
+- **Image**: [Link to X-ray image]
+
+## Download and Usage
+
+The dataset can be downloaded from [Hugging Face datasets page](https://huggingface.co/datasets/WorldMedQA/V). All code for handling and evaluating the dataset is available in the following repositories:
+- **Dataset Code**: [WorldMedQA GitHub repository](https://github.com/WorldMedQA/V)
+- **Evaluation Code**: [VLMEvalKit GitHub repository](https://github.com/WorldMedQA/VLMEvalKit/tree/main)
+
+## Citation
+
+Please cite this dataset as follows:
+
+```bibtex
+@article{WorldMedQA-V2024,
+  title={WorldMedQA-V: A Multilingual, Multimodal Medical Examination Dataset},
+  author={João Matos et al.},
+  journal={Preprint},
+  year={2024},
+}