# Healix-V1 Dataset 

## Description

Healix-V1 is a rich and diverse dataset consisting of 809k Question-Answer pairs within the medical domain. This dataset has been meticulously curated to fuel research initiatives in the areas of medical language understanding, medical dialogue systems, and knowledge extraction. Healix-V1 serves as a valuable resource for developing and improving machine learning models for healthcare applications, enabling them to understand and generate human-like responses in medical context The dataset follows the format used in ALPACA model fine-tuning:

```plaintext
### Input:
Question
### Response:
Answer

## Data Sources

The dataset has been compiled from a variety of valuable and authoritative sources, each contributing different kinds of medical question-answer pairs:

1. **Medical books**: 426,241 QA pairs - These pairs are derived from an array of reputable medical books. The questions were extracted and provided as prompts to GPT-3.5, which in turn generated the corresponding answers.

2. **[jianghc/medical_chatbot](URL)**: 46,867 QA pairs - This is a dataset derived from a medical chatbot project. 

3. **The Medical Question and Answering dataset(MQuAD)**: 23,802 QA pairs - MQuAD is a medical dataset specifically designed for the task of question answering.

4. **PubMed**: 1,000 QA pairs - These are pairs extracted from the extensive library of medical articles on PubMed.

5. **GenMedGPT**: 5,000 QA pairs - Derived from the GenMedGPT project aimed at generating medical language.

6. **iCliniq**: 7,321 QA pairs - iCliniq is a platform where users ask health-related questions which are answered by certified doctors.

7. **HealthCareMagic**: 100,000 QA pairs - HealthCareMagic is an interactive health platform with a vast amount of user-generated medical QAs.

8. **medical_meadow_wikidoc**: 10,000 QA pairs - These pairs are extracted from WikiDoc, a free medical textbook.

9. **medical_meadow_wikidoc_medical_flashcards**: 33,955 QA pairs - Medical flashcards provide concise medical information in a Q&A format.

10. **MedQA-USMLE-4-options**: 10,178 QA pairs - These are QAs similar to the format of the USMLE exam for medical licensing in the U.S.

## Potential Applications

Healix-V1 can serve a multitude of purposes such as:

- Training AI models for medical chatbots
- Developing advanced search engines for medical databases
- Creating tutoring systems for medical students
- Enhancing automated patient assistance systems
- Helping in developing systems for medical examination preparation

## Data Length Distribution

- (0.0, 256.0]: 96.724181%
- (256.0, 512.0]: 2.903792%
- (512.0, 768.0]: 0.299476%
- (768.0, 1024.0]: 0.050675%
- (1024.0, 2048.0]: 0.018910%

## Metadata

- **License:** ODC-BY
- **Language:** English
- **Tags:** Biology, Medical
- **Size Categories:** 100K<n<1M

## Dataset Info

- **Features:**
    - name: text
    - dtype: string
- **Splits:**
    - name: train
    - num_bytes: 419605911
    - num_examples: 798902
- **Download Size:** 209261302 bytes
- **Dataset Size:** 419605911 bytes
size_categories:100K<n<1M language:en license:odc-by biology medical region:us
{"language": ["en"], "license": "odc-by", "size_categories": ["100K<n<1M"], "dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 427613608, "num_examples": 796239}], "download_size": 213902701, "dataset_size": 427613608}, "tags": ["biology", "medical"]}
TAGS
#size_categories-100K<n<1M #language-English #license-odc-by #biology #medical #region-us 

# Healix-V1 Dataset 

## Description

Healix-V1 is a rich and diverse dataset consisting of 809k Question-Answer pairs within the medical domain. This dataset has been meticulously curated to fuel research initiatives in the areas of medical language understanding, medical dialogue systems, and knowledge extraction. Healix-V1 serves as a valuable resource for developing and improving machine learning models for healthcare applications, enabling them to understand and generate human-like responses in medical context The dataset follows the format used in ALPACA model fine-tuning:

'''plaintext
### Input:
Question
### Response:
Answer

## Data Sources

The dataset has been compiled from a variety of valuable and authoritative sources, each contributing different kinds of medical question-answer pairs:

1. Medical books: 426,241 QA pairs - These pairs are derived from an array of reputable medical books. The questions were extracted and provided as prompts to GPT-3.5, which in turn generated the corresponding answers.

2. jianghc/medical_chatbot: 46,867 QA pairs - This is a dataset derived from a medical chatbot project. 

3. The Medical Question and Answering dataset(MQuAD): 23,802 QA pairs - MQuAD is a medical dataset specifically designed for the task of question answering.

4. PubMed: 1,000 QA pairs - These are pairs extracted from the extensive library of medical articles on PubMed.

5. GenMedGPT: 5,000 QA pairs - Derived from the GenMedGPT project aimed at generating medical language.

6. iCliniq: 7,321 QA pairs - iCliniq is a platform where users ask health-related questions which are answered by certified doctors.

7. HealthCareMagic: 100,000 QA pairs - HealthCareMagic is an interactive health platform with a vast amount of user-generated medical QAs.

8. medical_meadow_wikidoc: 10,000 QA pairs - These pairs are extracted from WikiDoc, a free medical textbook.

9. medical_meadow_wikidoc_medical_flashcards: 33,955 QA pairs - Medical flashcards provide concise medical information in a Q&A format.

10. MedQA-USMLE-4-options: 10,178 QA pairs - These are QAs similar to the format of the USMLE exam for medical licensing in the U.S.

## Potential Applications

Healix-V1 can serve a multitude of purposes such as:

- Training AI models for medical chatbots
- Developing advanced search engines for medical databases
- Creating tutoring systems for medical students
- Enhancing automated patient assistance systems
- Helping in developing systems for medical examination preparation

## Data Length Distribution

- (0.0, 256.0]: 96.724181%
- (256.0, 512.0]: 2.903792%
- (512.0, 768.0]: 0.299476%
- (768.0, 1024.0]: 0.050675%
- (1024.0, 2048.0]: 0.018910%

## Metadata

- License: ODC-BY
- Language: English
- Tags: Biology, Medical
- Size Categories: 100K<n<1M

## Dataset Info

- Features:
    - name: text
    - dtype: string
- Splits:
    - name: train
    - num_bytes: 419605911
    - num_examples: 798902
- Download Size: 209261302 bytes
- Dataset Size: 419605911 bytes
# Healix-V1 Dataset ## Description

Healix-V1 is a rich and diverse dataset consisting of 809k Question-Answer pairs within the medical domain. This dataset has been meticulously curated to fuel research initiatives in the areas of medical language understanding, medical dialogue systems, and knowledge extraction. Healix-V1 serves as a valuable resource for developing and improving machine learning models for healthcare applications, enabling them to understand and generate human-like responses in medical context The dataset follows the format used in ALPACA model fine-tuning:

'''plaintext ### Input:
Question ### Response:
Answer ## Data Sources

The dataset has been compiled from a variety of valuable and authoritative sources, each contributing different kinds of medical question-answer pairs:

1. Medical books: 426,241 QA pairs - These pairs are derived from an array of reputable medical books. The questions were extracted and provided as prompts to GPT-3.5, which in turn generated the corresponding answers.

2. jianghc/medical_chatbot: 46,867 QA pairs - This is a dataset derived from a medical chatbot project. 

3. The Medical Question and Answering dataset(MQuAD): 23,802 QA pairs - MQuAD is a medical dataset specifically designed for the task of question answering.

4. PubMed: 1,000 QA pairs - These are pairs extracted from the extensive library of medical articles on PubMed.

5. GenMedGPT: 5,000 QA pairs - Derived from the GenMedGPT project aimed at generating medical language.

6. iCliniq: 7,321 QA pairs - iCliniq is a platform where users ask health-related questions which are answered by certified doctors.

7. HealthCareMagic: 100,000 QA pairs - HealthCareMagic is an interactive health platform with a vast amount of user-generated medical QAs.

8. medical_meadow_wikidoc: 10,000 QA pairs - These pairs are extracted from WikiDoc, a free medical textbook.

9. medical_meadow_wikidoc_medical_flashcards: 33,955 QA pairs - Medical flashcards provide concise medical information in a Q&A format.

10. MedQA-USMLE-4-options: 10,178 QA pairs - These are QAs similar to the format of the USMLE exam for medical licensing in the U.S. ## Potential Applications

Healix-V1 can serve a multitude of purposes such as:

- Training AI models for medical chatbots
- Developing advanced search engines for medical databases
- Creating tutoring systems for medical students
- Enhancing automated patient assistance systems
- Helping in developing systems for medical examination preparation ## Data Length Distribution

- (0.0, 256.0]: 96.724181%
- (256.0, 512.0]: 2.903792%
- (512.0, 768.0]: 0.299476%
- (768.0, 1024.0]: 0.050675%
- (1024.0, 2048.0]: 0.018910% ## Metadata

- License: ODC-BY
- Language: English
- Tags: Biology, Medical
- Size Categories: 100K<n<1M ## Dataset Info

- Features:
    - name: text
    - dtype: string
- Splits:
    - name: train
    - num_bytes: 419605911
    - num_examples: 798902
- Download Size: 209261302 bytes
- Dataset Size: 419605911 bytes
TAGS
#size_categories-100K<n<1M #language-English #license-odc-by #biology #medical #region-us 
 # Healix-V1 Dataset ## Description

Healix-V1 is a rich and diverse dataset consisting of 809k Question-Answer pairs within the medical domain. This dataset has been meticulously curated to fuel research initiatives in the areas of medical language understanding, medical dialogue systems, and knowledge extraction. Healix-V1 serves as a valuable resource for developing and improving machine learning models for healthcare applications, enabling them to understand and generate human-like responses in medical context The dataset follows the format used in ALPACA model fine-tuning:

'''plaintext ### Input:
Question ### Response:
Answer ## Data Sources

The dataset has been compiled from a variety of valuable and authoritative sources, each contributing different kinds of medical question-answer pairs:

1. Medical books: 426,241 QA pairs - These pairs are derived from an array of reputable medical books. The questions were extracted and provided as prompts to GPT-3.5, which in turn generated the corresponding answers.

2. jianghc/medical_chatbot: 46,867 QA pairs - This is a dataset derived from a medical chatbot project. 

3. The Medical Question and Answering dataset(MQuAD): 23,802 QA pairs - MQuAD is a medical dataset specifically designed for the task of question answering.

4. PubMed: 1,000 QA pairs - These are pairs extracted from the extensive library of medical articles on PubMed.

5. GenMedGPT: 5,000 QA pairs - Derived from the GenMedGPT project aimed at generating medical language.

6. iCliniq: 7,321 QA pairs - iCliniq is a platform where users ask health-related questions which are answered by certified doctors.

7. HealthCareMagic: 100,000 QA pairs - HealthCareMagic is an interactive health platform with a vast amount of user-generated medical QAs.

8. medical_meadow_wikidoc: 10,000 QA pairs - These pairs are extracted from WikiDoc, a free medical textbook.

9. medical_meadow_wikidoc_medical_flashcards: 33,955 QA pairs - Medical flashcards provide concise medical information in a Q&A format.

10. MedQA-USMLE-4-options: 10,178 QA pairs - These are QAs similar to the format of the USMLE exam for medical licensing in the U.S. ## Potential Applications

Healix-V1 can serve a multitude of purposes such as:

- Training AI models for medical chatbots
- Developing advanced search engines for medical databases
- Creating tutoring systems for medical students
- Enhancing automated patient assistance systems
- Helping in developing systems for medical examination preparation ## Data Length Distribution

- (0.0, 256.0]: 96.724181%
- (256.0, 512.0]: 2.903792%
- (512.0, 768.0]: 0.299476%
- (768.0, 1024.0]: 0.050675%
- (1024.0, 2048.0]: 0.018910% ## Metadata

- License: ODC-BY
- Language: English
- Tags: Biology, Medical
- Size Categories: 100K<n<1M ## Dataset Info

- Features:
    - name: text
    - dtype: string
- Splits:
    - name: train
    - num_bytes: 419605911
    - num_examples: 798902
- Download Size: 209261302 bytes
- Dataset Size: 419605911 bytes
passage: TAGS
#size_categories-100K<n<1M #language-English #license-odc-by #biology #medical #region-us 
# Healix-V1 Dataset## Description

Healix-V1 is a rich and diverse dataset consisting of 809k Question-Answer pairs within the medical domain. This dataset has been meticulously curated to fuel research initiatives in the areas of medical language understanding, medical dialogue systems, and knowledge extraction. Healix-V1 serves as a valuable resource for developing and improving machine learning models for healthcare applications, enabling them to understand and generate human-like responses in medical context The dataset follows the format used in ALPACA model fine-tuning:

'''plaintext### Input:
Question### Response:
Answer