Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
medical
File size: 1,647 Bytes
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---
language:
- en
size_categories:
- 10K<n<100K
task_categories:
- question-answering
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
- name: instruction
dtype: string
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 49472054
num_examples: 16359
download_size: 18071045
dataset_size: 49472054
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- medical
---
Dataset made for instruction supervised finetuning of Llama 3 LLMs based on the Medquad dataset:
- Medquad dataset (https://www.kaggle.com/datasets/jpmiller/layoutlm)
## Medquad
MedQuAD is a comprehensive collection consisting of 47,457 medical question-answer pairs compiled from 12 authoritative sources within the National Institutes of Health (NIH), including domains like cancer.gov, niddk.nih.gov, GARD, and MedlinePlus Health Topics. These question-answer pairs span 37 distinct question types, covering a wide spectrum of medical subjects, including diseases, drugs, and medical procedures. The dataset features additional annotations provided in XML files, facilitating various Information Retrieval (IR) and Natural Language Processing (NLP) tasks. These annotations encompass crucial information such as question type, question focus, synonyms, Unique Identifier (CUI) from the Unified Medical Language System (UMLS), and Semantic Type. Moreover, the dataset includes categorization of question focuses into three main categories: Disease, Drug, or Other, with the exception of collections from MedlinePlus, which exclusively focus on diseases. |