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