README.md

metadata

annotations_creators:
  - found
language_creators:
  - expert-generated
  - found
languages:
  en:
    - en
  zh:
    - zh
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  en:
    - n<1K
  zh:
    - 1K<n<10K
source_datasets:
  - original
task_categories:
  - question-answering
task_ids:
  - closed-domain-qa
paperswithcode_id: null

Dataset Card for [Dataset Name]

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• 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
  • Contributions

Dataset Description

• Homepage: https://github.com/UCSD-AI4H/COVID-Dialogue
• Repository: The data is also present in the same GIT repository
• Paper: https://pengtaoxie.github.io/coviddiag.pdf
• Leaderboard:
• Point of Contact:

Dataset Summary

COVID-Dialogue-Dataset-English is an English medical dialogue dataset about COVID-19 and other types of pneumonia. Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice. There are 603 consultations.

COVID-Dialogue-Dataset-Chinese is a Chinese medical dialogue dataset about COVID-19 and other types of pneumonia. Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice. There are 1393 consultations.

The dataset is present as a single text file. COVID-Dialogue-Dataset-Chinese.txt for Chinese and COVID-Dialogue-Dataset-English.txt for English.

Supported Tasks and Leaderboards

Used for QA tasks. There is also a COVID-19 dialogue generation model available for the Chinese Data. The pre-print and more information is available in this arxiv pre-print.

Languages

Monolingual. The datasets are in English (EN) and Chinese (ZH)

Dataset Structure

Data Instances

An example of dialogue is:

{
    'dialogue_id': 602, 
    'dialogue_url': 'https://www.healthtap.com/member/fg?page=/search/covid', 
    'dialogue_turns': [{'speaker': 'Patient', 
                'utterance': 'Can coronavirus symptoms be mild for some people versus severe? For example, could it just involve being very fatigued, low grade fever for a few days and not the extreme symptoms? Or is it always a full blown cold and struggle to breathe?Can coronavirus symptoms be mild for some people versus severe? For example, could it just involve being very fatigued, low grade fever for a few days and not the extreme symptoms? Or is it always a full blown cold and struggle to breathe?'}, 
                           {'speaker': 'Doctor', 
                            'utterance': 'In brief:   Symptoms vary.   Some may have no symptoms at all. Some can be life threatening.   Would you like to video or text chat with me?'}]
}

The dataset is built from icliniq.com, healthcaremagic.com, healthtap.com and all copyrights of the data belong to these websites. (for English)

The dataset is built from Haodf.com and all copyrights of the data belong to Haodf.com. (for Chinese)

Data Fields

Each consultation consists of the below:

• ID
• URL
• Description of patient’s medical condition
• Dialogue
• Diagnosis and suggestions (Optional, mostly for Chinese)

For generating the QA only the below fields have been considered:

• ID : Consultatation Identifier (restarts for each file)
• URL: The url link of the extracted conversation
• Dialogue : The conversation between the doctor and the patient.

These are arranged as below in the prepared dataset. Each item will be represented with these parameters.

• "file_name": string - signifies the file from which the conversation was extracted
• "dialogue_id": int32 - the dialogue id
• "dialogue_url": string - url of the conversation
• "dialogue_turns": datasets.Sequence - sequence of dialogues between patient and the doctor.Consists ClassLabel(names=["病人", "医生"]), and "utterance"(string) for each turn. (ClassLable(names=["Patient", "Doctor"]) for english)

Data Splits

There are no data splits on the original data

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@article{ju2020CovidDialog, title={CovidDialog: Medical Dialogue Datasets about COVID-19}, author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao}, journal={ https://github.com/UCSD-AI4H/COVID-Dialogue}, year={2020} }

Contributions

Thanks to @vrindaprabhu for adding this dataset.