---
dataset_info:
  features:
  - name: input
    dtype: string
  - name: output
    dtype: string
  - name: instruction
    dtype: string
  - name: prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 49831952
    num_examples: 16359
  download_size: 18149871
  dataset_size: 49831952
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- question-answering
tags:
- medical
size_categories:
- 10K<n<100K
---

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.