alibayram/turkish-hospital-medical-articles

🏥 Turkish Hospital Medical Articles Dataset

A comprehensive collection of Turkish-language medical articles from 14 major hospital and healthcare provider websites in Turkey. This dataset is designed for training and evaluating Turkish NLP models in the medical domain, including large language models (LLMs), health chatbots, medical text summarization, and clinical text classification.

📊 Dataset Overview

• Total Articles: ~24,612 medical articles
• Sources: 14 major Turkish hospitals and healthcare providers
• Language: Turkish (tr)
• Format: Parquet files (one per hospital)
• License: CC BY 4.0
• Total Size: ~95MB

🏥 Included Hospital Sources

Hospital	Dataset Split	Description
Acıbadem Hospital	acibadem	Leading private hospital network
Anadolu Sağlık	anadolusaglik	Comprehensive healthcare provider
Atlas Hospital	atlas	Specialized medical center
Başkent İstanbul	baskentistanbul	University hospital network
Bayındır Hospital	bayindir	Private healthcare institution
Florence Nightingale	florence	Specialized hospital network
Güven Hospital	guven	Private medical center
Liv Hospital	liv	International healthcare provider
Medical Park	medicalpark	Private hospital network
Medical Point	medicalpoint	Specialized medical facility
Medicana Hospitals	medicana	Large hospital network
Medipol University Hospital	medipol	University medical center
Memorial Hospital	memorial	Private healthcare network
Yeditepe University	yeditepe	University hospital

📋 Data Schema

Each article in the dataset contains the following fields:

Field	Type	Description
url	string	Original article URL
title	string	Article title
text	string	Full article content
publish_date	string	Original publication date
update_date	string	Last update date
scrape_date	string	Date when article was collected

🚀 Usage Examples

Load the entire dataset:

from datasets import load_dataset

# Load all hospital data
dataset = load_dataset("alibayram/turkish-hospital-medical-articles", token="your_token")

# Access specific hospital data
acibadem_data = dataset["acibadem"]
memorial_data = dataset["memorial"]

Load specific hospitals:

from datasets import load_dataset

# Load only specific hospitals
selected_hospitals = {
    "acibadem": "acibadem.parquet",
    "memorial": "memorial.parquet",
    "medicana": "medicana.parquet"
}

dataset = load_dataset("alibayram/turkish-hospital-medical-articles",
                      data_files=selected_hospitals,
                      token="your_token")

Access article examples:

# Get first article from Acıbadem
first_article = dataset["acibadem"][0]
print(f"Title: {first_article['title']}")
print(f"Content: {first_article['text'][:200]}...")
print(f"Published: {first_article['publish_date']}")

🎯 Use Cases

Medical NLP Applications:

• Medical Text Classification: Categorize articles by medical specialty
• Health Information Extraction: Extract symptoms, treatments, and medical procedures
• Medical Question Answering: Train models to answer health-related questions
• Medical Text Summarization: Create concise summaries of medical articles
• Health Chatbot Training: Develop Turkish medical chatbots
• Clinical Text Analysis: Analyze medical terminology and concepts

Research Applications:

• Medical Language Modeling: Train Turkish medical LLMs
• Healthcare Information Retrieval: Build medical search systems
• Medical Knowledge Graph Construction: Extract medical entities and relationships
• Cross-hospital Analysis: Compare medical content across different institutions

🔧 Data Processing

The dataset has been processed to:

• Remove unnecessary columns (headings, source metadata)
• Standardize date fields
• Ensure consistent schema across all hospital sources
• Maintain original article content integrity

📈 Dataset Statistics

• Total Articles: 24,612
• Average Article Length: ~500-2000 words
• Date Range: Various (based on hospital website content)
• Medical Topics Covered:
  • General medicine
  • Specialized treatments
  • Health tips and advice
  • Medical procedures
  • Disease information
  • Wellness and prevention

⚠️ Important Notes

1. Medical Disclaimer: This dataset contains medical information but should not be used for clinical decision-making
2. Language: All content is in Turkish
3. Source Attribution: Articles are from official hospital websites
4. Privacy: No personal patient information is included
5. Accuracy: Content accuracy depends on the original hospital websites

🤝 Contributing

This dataset is based on the original work by umutertugrul and has been processed and organized for improved usability.

📄 License

This dataset is licensed under the Creative Commons Attribution 4.0 International License.

🙏 Acknowledgments

• Original data collection by umutertugrul
• Hospital websites for providing public medical content
• Hugging Face for hosting the dataset

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For questions or issues, please open an issue on the dataset page.