README.md

---
license: mit
language:
- en
tags:
- medical
size_categories:
- 10K<n<100K
task_categories:
- question-answering
pretty_name: Recurv Medical Dataset
---

# 🩺 Recurv-Medical-Dataset:
[![License](https://img.shields.io/badge/license-MIT-blue?style=flat-square)](https://opensource.org/license/MIT)
[![HF](https://img.shields.io/badge/HuggingFace-Recurv--Medical--Dataset-yellow?style=flat-square&logo=huggingface)](https://huggingface.co/RecurvAI/Recurv-Medical-Dataset)


The **Recurv-Medical-Dataset** is a comprehensive resource of 67,299 high-quality question-answer pairs explicitly designed for training and fine-tuning medical AI models. Curated from trusted medical sources, this dataset focuses on real-world scenarios like anamnesis, diagnostics, and treatment recommendations. It sets a new benchmark for advancing conversational AI in the healthcare domain.

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## 📈 **Dataset Statistics**

| **Feature**                 | **Value**       |
|-----------------------------|-----------------|
| Number of QA Pairs          | 67,299          |
| Average Question Length     | 420             |
| Average Answer Length       | 603             |

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## 📜 **Data Sources**

Sourced from the most **authoritative and trusted references** in medical fields:  
* **PubMed and Open Access Journals**  
* **Clinical Practice Guidelines (WHO, CDC)**  
* **Medical Textbooks**  
* **EHR-Simulated Data**  
* **Peer-Reviewed Research Papers**  

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## 🙌 **Contributing**

We welcome contributions to enhance Recurv-Medical-Dataset. You can:
- Share feedback or suggestions on the Hugging Face Model Hub
- Submit pull requests or issues for model improvement.

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## 📜 **License**

This model is licensed under the **MIT License**.

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## 📞 **Community**

For questions or support, connect with us via:
- **Twitter**: [RecurvAI](https://x.com/recurvai)
- **Email**: [[email protected]](mailto:[email protected])

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## 🤝 **Acknowledgments**

Special thanks to the medical community and researchers for their valuable insights and support in building this model. Together, we’re advancing AI in healthcare.