Datasets:
license: cc-by-4.0
language:
- en
pretty_name: MedQuAD - Medical QA Dataset
size_categories:
- 10K<n<100K
MedQuAD - Medical Question Answering Dataset
Dataset Overview
MedQuAD (Medical Question Answering Dataset) is a collection of 16,407 medical question-answer pairs derived from 9 NIH websites. It covers 37 question types related to diseases, drugs, medical tests, and treatments. This dataset is useful for building medical question-answering models, retrieval-augmented generation (RAG) systems, and other NLP applications in the healthcare domain.
Dataset Structure
The dataset is stored in CSV format with the following columns:
| Column Name | Description |
|---|---|
| text | A formatted string that includes both the question and answer. |
| query | The question asked. |
| answers | The corresponding answer. |
| topic_embeddings | Placeholder for clustering or topic embeddings. (Default: -1) |
| group_name | The medical category of the question-answer pair. |
Example Entry
text: <HUMAN>: What is (are) Adult Acute Lymphoblastic Leukemia ?
<ASSISTANT>: Key Points
- Adult acute lymphoblastic leukemia (ALL) is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell).....
query: What is (are) Adult Acute Lymphoblastic Leukemia ?
answers: Key Points
- Adult acute lymphoblastic leukemia (ALL) is a type of cancer in which the bone marrow makes too many lymphocytes (a type of white blood cell). ...
topic_embeddings: 1
group_name: 1_CancerGov_QA
Usage
You can load the dataset using Hugging Face Datasets Library:
from datasets import load_dataset
dataset = load_dataset("mukulb/clustered_MEDQUAD_dataset_with_groups")
print(dataset["train"][0])
Applications
- Medical Question-Answering Systems
- Retrieval-Augmented Generation (RAG) for Healthcare
- Named Entity Recognition (NER) for Medical Concepts
- Semantic Search and Information Retrieval
License
The dataset is available for research purposes only. Please refer to individual source websites for copyright information. https://github.com/abachaa/MedQuAD.git
Contribution
If you have any improvements or suggestions, feel free to open an issue or contribute via a pull request!
Maintained by: [Mukul Bedwa]
📧 Contact: [mukulbedwa.jrf01@iiitu.ac.in]
🚀 Hosted on Hugging Face: [your_hf_mukulbedwa/MedQuAD]