umutertugrul/turkish-hospital-medical-articles

🏥 Turkish Medical Articles from 14 Hospital Websites

This dataset contains Turkish-language medical articles scraped from 14 official hospital and healthcare provider websites in Turkey. Each file corresponds to one source and is stored in efficient .parquet format.

It is designed for training and evaluating Turkish NLP models in the medical domain, including large language models (LLMs), health chatbots, summarizers, and classifiers.

🧾 Total articles: ~ 25,000
📦 Total file size: ~95MB
🗂️ Format: .parquet
👤 Curated by: umutertugrul
🔓 License: CC BY 4.0

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🏷️ Included Sources

Filename	Source Institution
acibadem.parquet	Acıbadem Hospital
anadolusaglik.parquet	Anadolu Sağlık
atlas.parquet	Atlas Hospital
baskentistanbul.parquet	Başkent İstanbul
bayindir.parquet	Bayındır Hospital
florence.parquet	Florence Nightingale
guven.parquet	Güven Hospital
liv.parquet	Liv Hospital
medicalpark.parquet	Medical Park
medicalpoint.parquet	Medical Point
medicana.parquet	Medicana Hospitals
medipol.parquet	Medipol University Hospital
memorial.parquet	Memorial Hospital
yeditepe.parquet	Yeditepe University

Each file contains articles specific to that institution, covering a wide range of medical topics and specialties.

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🔤 Schema

Each .parquet file may contain the following fields:

• url: Original article URL
• title: Title of the article
• headings: Section headings or subtopics (if available)
• text: Full body content of the article
• publish_date: Date the article was originally published
• update_date: Last updated date (if available)
• scrape_date: Date when the article was collected
• __source: Hospital/source name (automatically added during conversion)

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🚀 Example Usage

from datasets import load_dataset, Features, Value

files = {
    "acibadem": "acibadem.parquet",
    "anadolusaglik": "anadolusaglik.parquet",
    "atlas": "atlas.parquet",
    "baskentistanbul": "baskentistanbul.parquet",
    "bayindir": "bayindir.parquet",
    "florence": "florence.parquet",
    "guven": "guven.parquet",
    "liv": "liv.parquet",
    "medicalpark": "medicalpark.parquet",
    "medicalpoint": "medicalpoint.parquet",
    "medicana": "medicana.parquet",
    "medipol": "medipol.parquet",
    "memorial": "memorial.parquet",
    "yeditepe": "yeditepe.parquet"
}

features = Features({
    "url": Value("string"),
    "title": Value("string"),
    "headings": Value("string"),
    "text": Value("string"),
    "publish_date": Value("string"),
    "update_date": Value("string"),
    "scrape_date": Value("string"),
    "__source": Value("string") 
})

ds_healthcare_1 = load_dataset(
    "umutertugrul/turkish-hospital-medical-articles",
    data_files=files,
    features=features
)