README.md

metadata

annotations_creators:
  - no-annotation
language:
  - en
language_creators:
  - found
  - other
license:
  - mit
multilinguality:
  - monolingual
pretty_name: MedQA Textbook (English) Corpus
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|medmcqa
tags:
  - medical
  - clinical medicine
  - biology
task_categories:
  - text-generation
task_ids:
  - language-modeling

Dataset Card for MedQA English Textbooks

Table of Contents

• Dataset Description
  • Dataset Summary
  • Languages
• Dataset Structure
  • Data Instances
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information

Dataset Description

Dataset Summary

MedQA Textbook (English) with focused emphasis on domain of Clinical Medicine and other subsets relevant for use with training medical LLMs with gold standard domain text.

Languages

English

Dataset Structure

Data Instances

Records have the following structure

{"text": "The manifestations of acute intestinal obstruction depend on the nature of the underlying disease process, [..]", 
 "source": "textbooks/en/InternalMed_Harrison.txt"}

Dataset Creation

Curation Rationale

The MedQA dataset includes raw text corpus that is excluded from most of the datasets derived and the raw text is valuable for pre-training of medical LLMS

Source Data

Initial Data Collection and Normalization

Langchain's RecursiveCharacterTextSplitter is used for chunking and the most commonly-appearing non-ASCII characters are replaced with readable equivalents. The texts are then broken into separate subsets:

• Core Clinical Medicine
• Basic Biology
• Pharmacology
• Psychiatry