task_categories:text-generation language:zh license:apache-2.0 size_categories:1M<n<10M format:json modality:text library:datasets library:dask library:mlcroissant region:us medical
---
license: apache-2.0
task_categories:
- text-generation
language:
- zh
tags:
- medical
size_categories:
- 1M<n<10M
---
# MedicalQA-1.4M
MedicalQA is an integrated large-scale, high-quality Chinese SFT dataset, designed for medical knowledge injection into LLMs by SFT or RAG. 

Each sample is reviewed by the free LLM (ERNIE-Speed) using our proposed Quality Evaluation Algorithm.

MedArk-KI involving in two types of medical knowledge: Traditional Chinese Medicine (TCM) and Western Medicine(WM). It consists of 4 subsets as shown in the tabel: 

| Name | Volume  | Author    | Reviewer    | Type | Source                  | Source Format          |
|------|---------|-----------|-------------|------|-------------------------|-----------------|
| DX   | 5,3554  | Doctor    | Doctor      |  WM  | Web                     | HTML            |
| HT   | 135,8093| ChatGPT   | ERNIE-Speed |  WM  | Books, Encyclopedia, Web| PDF, TXT, HTML  |
| TCM  | 3,8294  | ERNIE 4.0 | ERNIE-Speed | TCM  | Books, KG               | PDF, Latex, JSON|
| MB   | 1,4543  |ERNIE-Speed|ERNIE-Speed  |  WM  | Books                   | Latex           |
|Totol | 146,4484|           |             |      |                         |                 |

# 1.DX

A total of 5,3554 high-quality Q&A pairs were collected from the DingXiang website, 丁香医生 (https://dxy.com/diseases), and underwent rigorous data cleaning. 
Each answer was authored by a doctor and reviewed by another doctor, ensuring that all information is accurate and reliable. 
These Q&A pairs encompass 8 key areas of medical knowledge across 3412 diseases in 31 departments: disease introduction, symptoms, causes, diagnosis, treatment, lifestyle, prevention, and consultation guidance.


# 2.HT


https://huggingface.co/datasets/FreedomIntelligence/HuatuoGPT2-Pretraining-Instruction

Medical_Web_Corpus_cn
Medical_Encyclopedia_cn
Medical_Books_cn

# 3.TCM

https://www.dayi.org.cn/

![image/png](https://cdn-uploads.huggingface.co/production/uploads/672af27475d62cdf4e85815a/5UBlT5Aw4eZW88_QXl2UC.png)


# 4.MB

https://github.com/scienceasdf/medical-books