--- task_categories: - question-answering language: - en - he - ja - es - pt tags: - medical size_categories: - n<1K --- # WorldMedQA-V: A Multilingual, Multimodal Medical Examination Dataset logo ## 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 see below] - **Options**: - A: Aspergilose pulmonar - B: Carcinoma pulmonar - C: Tuberculose cavitária - D: Bronquiectasia com infecção - **Correct Answer**: B ![example](src/example.png) ### Evaluate models/results: ![results](src/results.png) ## 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={Matos and Chen et al.}, journal={Preprint}, year={2024}, }