|
--- |
|
task_categories: |
|
- question-answering |
|
language: |
|
- en |
|
tags: |
|
- medical |
|
pretty_name: Med_data |
|
size_categories: |
|
- 100K<n<1M |
|
--- |
|
|
|
# Complete Dataset |
|
|
|
Data shown below is complete Medical dataset |
|
|
|
Access the complete dataset using the link below: |
|
|
|
[Download Dataset](https://fp2s.short.gy/Med_datasets) |
|
|
|
# Support Us on Product Hunt and X! |
|
|
|
| [<a href="https://www.producthunt.com/posts/medical_datasets?embed=true&utm_source=badge-featured&utm_medium=badge&utm_souce=badge-medical_datasets" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=754666&theme=light&t=1738501085565" alt="Medical_Datasets - Empowering healthcare innovation with data-driven insights | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>](https://www.producthunt.com/posts/medical_datasets) | [<img src="https://upload.wikimedia.org/wikipedia/commons/2/2d/Twitter_X.png" width="40">](https://x.com/PitchdeckEngine) | |
|
|
|
# Connect with Me on Happenstance |
|
|
|
Join me on Happenstance! |
|
[Click here to add me as a friend](https://happenstance.ai/invite/friend/y5OCIMc4sLNjSuMCFyyVtLxAoYU) |
|
|
|
Looking forward to connecting! |
|
|
|
For more information or assistance, feel free to contact us at **harryjosh242@gmail.com**. |
|
|
|
 |
|
|
|
short_description: Medical datasets for healthcare model training. |
|
--- |
|
|
|
# **Medical Datasets** |
|
|
|
This Medical dataset is crafted as a versatile resource for enthusiasts of data science, machine learning, and data analysis. It replicates the characteristics of real-world healthcare data, offering users a platform to practice, refine, and showcase their data manipulation and analytical skills within the healthcare domain. |
|
|
|
## **Potential Uses** |
|
- Building and testing predictive models specific to healthcare. |
|
- Practicing techniques for data cleaning, transformation, and analysis. |
|
- Designing visualizations to uncover insights into healthcare trends. |
|
- Learning and teaching data science and machine learning concepts in a healthcare setting. |
|
|
|
## **Acknowledgments** |
|
- This dataset is entirely synthetic, created with a focus on respecting healthcare data privacy and security. It contains no real patient information and complies with privacy regulations. |
|
- The goal is to support advancements in data science and healthcare analytics while inspiring innovative ideas. |
|
|
|
## Directory Structure |
|
|
|
├── evaluation-medical-instruction-datasets/ |
|
│ ├── evaluation-medical-instruction-dataset.json |
|
│ ├── medmcqa-train-instruction-dataset.json |
|
│ ├── medqa-train-instruction-dataset.json |
|
│ └── pubmedqa-train-instruction-train.json |
|
├── general-medical-instruction-datasets/ |
|
│ ├── general-medical-instruction-dataset.json |
|
│ ├── GenMedGPT-5k.json |
|
│ ├── HealthCareMagic-100k.json |
|
│ ├── medical_meadow_wikidoc_medical_flashcards.json |
|
│ ├── medical_meadow_wikidoc_patient_info.json |
|
│ └── medicationqa.json |
|
├── medical-preference-data.json |
|
└── medical-pretraining-datasets/ |
|
|
|
## **Dataset Contents** |
|
|
|
### **Evaluation Medical Instruction Datasets** |
|
Contains datasets used for evaluating medical instruction models: |
|
- `evaluation-medical-instruction-dataset.json` |
|
- `medmcqa-train-instruction-dataset.json` |
|
- `medial-train-instruction-dataset.json` |
|
- `pubmedqa-train-instruction-train.json` |
|
|
|
### **General Medical Instruction Datasets** |
|
Contains general medical instruction datasets: |
|
- `general-medical-instruction-dataset.json` |
|
- `GenMedGPT-5k.json` |
|
- `HealthCareMagic-100k.json` |
|
- `medical_meadow_wikidoc_medical_flashcards.json` |
|
- `medical_meadow_wikidoc_patient_info.json` |
|
- `medicationqa.json` |
|
|
|
### **Medical Preference Data** |
|
- `medical-preference-data.json`: Contains data related to medical preferences. |
|
|
|
### **Medical Pretraining Datasets** |
|
Contains datasets used for pretraining medical models. |
|
|
|
### **quality_report** |
|
|
|
| Total | Missing Data (%) | Duplicate Rows (%) | Duplicate Rate (%) | Outlier Count | File Name | Error | |
|
|--------------|------------------|--------------------|--------------------|---------------|-----------------------------------------------|-------| |
|
| 2,000,000 | 0 | 114 | 0.03 | 0 | evaluation-medical-instruction-dataset.json | NaN | |
|
| 1,400,000 | 0 | 379 | 1.3 | 0 | general-medical-instruction-dataset.json | NaN | |
|
| 27,000 | 0 | 0 | 0 | 0 | GenMedGPT-5k.json | NaN | |
|
| 560,000 | 0 | 0 | 0 | 0 | HealthCareMagic-100k.json | NaN | |
|
| 169,000 | 0 | 427 | 1.26 | 0 | medical_meadow_wikidoc_medical_flashcards.json | NaN | |
|
| 29,000 | 0 | 92 | 1.55 | 0 | medical_meadow_wikidoc_patient_info.json | NaN | |
|
| 50,000 | 0 | 0 | 0 | 0 | medical_meadow_wikidoc.json | NaN | |
|
| 120,000 | 0 | 0 | 0 | 0 | medical-preference-data.json | NaN | |
|
| 2,700 | 0 | 0 | 0 | 0 | medicationqa.json | NaN | |
|
| 910,000 | 0 | 0 | 0 | 0 | medmcqa-train-instruction-dataset.json | NaN | |
|
| 50,000 | 0 | 0 | 0 | 0 | medqa-train-instruction-dataset.json | NaN | |
|
| 120,000 | 0 | 0 | 0 | 0 | open-platypus.json | NaN | |
|
| 400,000 | NaN | NaN | NaN | NaN | pmc_and_guidelines_and_pubmedqa_train.txt | NaN | |
|
| 200,000 | NaN | NaN | NaN | NaN | pmc_and_guidelines.txt | NaN | |
|
| 1,000,000 | 0 | 114 | 0.5 | 0 | pubmedqa-train-instruction-train.json | NaN | |
|
| 250,000 | 0 | 320 | 6.55 | 0 | umls_relation.json | NaN | |
|
| 240,000 | 0 | 0 | 0 | 0 | umls.json | NaN | |
|
|
|
|
|
 |
|
|
|
## **Usage** |
|
These datasets can be used to train and evaluate models for medical question answering and other related tasks. Each dataset is provided in **JSON** and **TXT** formats and contains various medical instructions, inputs, and outputs. |
|
|
|
## Example |
|
|
|
Here is an example entry from the `medicationqa.json` dataset: |
|
|
|
```json |
|
{ |
|
"instruction": "Your role as a doctor requires you to answer the medical questions taking into account the patient's description.", |
|
"input": "how fast does the medication take to work amlodipine", |
|
"output": "After oral administration of therapeutic doses of amlodipine besylate, absorption produces peak plasma concentrations between 6 and 12 hours." |
|
} |
|
|
|
|
|
|
