
# Dataset Card for WikiDoc
For the dataset containing patient information from wikidoc refer to [this dataset](https://huggingface.co/datasets/medalpaca/medical_meadow_wikidoc_patient_information)
## Dataset Description

- **Source:** https://www.wikidoc.org/index.php/Main_Page
- **Repository:** https://github.com/kbressem/medalpaca 
- **Paper:** TBA

### Dataset Summary
This dataset containes medical question-answer pairs extracted from [WikiDoc](https://www.wikidoc.org/index.php/Main_Page), 
a collaborative platform for medical professionals to share and contribute to up-to-date medical knowledge. 
The platform has to main subsites, the "Living Textbook" and "Patient Information". The "Living Textbook" 
contains chapters for various medical specialties, which we crawled. We then used GTP-3.5-Turbo to rephrase 
the paragraph heading to a question and used the paragraph as answer.  Patient Information is structured differently, 
in that each section subheading is already a question, making rephrasing them obsolete.  

**Note:** This dataset is still a WIP. While the Q/A pairs from the patient information seems to be mostly correct, 
the conversion using GPT-3.5-Turbo yielded some unsatisfactory results in  approximately 30% of cases. We are in the process of cleaning this dataset. 

### Citation Information
TBA
task_categories:question-answering language:en license:cc region:us
{"language": ["en"], "license": "cc", "task_categories": ["question-answering"]}
TAGS
#task_categories-question-answering #language-English #license-cc #region-us 


# Dataset Card for WikiDoc
For the dataset containing patient information from wikidoc refer to this dataset
## Dataset Description

- Source: URL
- Repository: URL 
- Paper: TBA

### Dataset Summary
This dataset containes medical question-answer pairs extracted from WikiDoc, 
a collaborative platform for medical professionals to share and contribute to up-to-date medical knowledge. 
The platform has to main subsites, the "Living Textbook" and "Patient Information". The "Living Textbook" 
contains chapters for various medical specialties, which we crawled. We then used GTP-3.5-Turbo to rephrase 
the paragraph heading to a question and used the paragraph as answer.  Patient Information is structured differently, 
in that each section subheading is already a question, making rephrasing them obsolete.  

Note: This dataset is still a WIP. While the Q/A pairs from the patient information seems to be mostly correct, 
the conversion using GPT-3.5-Turbo yielded some unsatisfactory results in  approximately 30% of cases. We are in the process of cleaning this dataset. 


TBA
# Dataset Card for WikiDoc
For the dataset containing patient information from wikidoc refer to this dataset ## Dataset Description

- Source: URL
- Repository: URL 
- Paper: TBA ### Dataset Summary
This dataset containes medical question-answer pairs extracted from WikiDoc, 
a collaborative platform for medical professionals to share and contribute to up-to-date medical knowledge. 
The platform has to main subsites, the "Living Textbook" and "Patient Information". The "Living Textbook" 
contains chapters for various medical specialties, which we crawled. We then used GTP-3.5-Turbo to rephrase 
the paragraph heading to a question and used the paragraph as answer.  Patient Information is structured differently, 
in that each section subheading is already a question, making rephrasing them obsolete.  

Note: This dataset is still a WIP. While the Q/A pairs from the patient information seems to be mostly correct, 
the conversion using GPT-3.5-Turbo yielded some unsatisfactory results in  approximately 30% of cases. We are in the process of cleaning this dataset. 


TBA
TAGS
#task_categories-question-answering #language-English #license-cc #region-us 
 # Dataset Card for WikiDoc
For the dataset containing patient information from wikidoc refer to this dataset ## Dataset Description

- Source: URL
- Repository: URL 
- Paper: TBA ### Dataset Summary
This dataset containes medical question-answer pairs extracted from WikiDoc, 
a collaborative platform for medical professionals to share and contribute to up-to-date medical knowledge. 
The platform has to main subsites, the "Living Textbook" and "Patient Information". The "Living Textbook" 
contains chapters for various medical specialties, which we crawled. We then used GTP-3.5-Turbo to rephrase 
the paragraph heading to a question and used the paragraph as answer.  Patient Information is structured differently, 
in that each section subheading is already a question, making rephrasing them obsolete.  

Note: This dataset is still a WIP. While the Q/A pairs from the patient information seems to be mostly correct, 
the conversion using GPT-3.5-Turbo yielded some unsatisfactory results in  approximately 30% of cases. We are in the process of cleaning this dataset. 


TBA
passage: TAGS
#task_categories-question-answering #language-English #license-cc #region-us 
# Dataset Card for WikiDoc
For the dataset containing patient information from wikidoc refer to this dataset## Dataset Description

- Source: URL
- Repository: URL 
- Paper: TBA### Dataset Summary
This dataset containes medical question-answer pairs extracted from WikiDoc, 
a collaborative platform for medical professionals to share and contribute to up-to-date medical knowledge. 
The platform has to main subsites, the "Living Textbook" and "Patient Information". The "Living Textbook" 
contains chapters for various medical specialties, which we crawled. We then used GTP-3.5-Turbo to rephrase 
the paragraph heading to a question and used the paragraph as answer.  Patient Information is structured differently, 
in that each section subheading is already a question, making rephrasing them obsolete.  

Note: This dataset is still a WIP. While the Q/A pairs from the patient information seems to be mostly correct, 
the conversion using GPT-3.5-Turbo yielded some unsatisfactory results in  approximately 30% of cases. We are in the process of cleaning this dataset. 


TBA