---
license: apache-2.0
language:
- tr
task_categories:
- question-answering
- text-classification
- text-generation
- text-retrieval
tags:
- medical
- text
size_categories:
- n<1K
dataset_info:
  features:
  - name: category
    dtype: string
  - name: topic
    dtype: string
  - name: text
    dtype: string
  - name: num_tokens
    dtype: int64
  splits:
  - name: train
    num_bytes: 14981996
    num_examples: 917
  download_size: 5518304
  dataset_size: 14981996
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Dataset Card for MedData_tr-1

This dataset has 917 instances and 5227389 tokens in total

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

- **Language(s) (NLP):** Turkish
- **License:** APACHE 2.0

### Dataset Sources

Memorial Health Library : https://www.memorial.com.tr/saglik-kutuphanesi

## Dataset Structure

**category** : The data was split into 3 categories 
- Tanı ve Testler (Diagnoses and Tests)
- Hastalıklar (Diseases)
- Tedavi Yöntemleri (Treatment Methods)

**topic** : The topic of the text content

**text** : Full text

**num_tokens** : Token count of the full text

## Dataset Creation

### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
This dataset was created to increase the Turkish medical text data in HuggingFace Datasets library.


### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
Memorial is a hospital network based in Turkey. Their website provides a health library, which the contents were written by doctors who are experts in their fields.


#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
The contents were scraped using Python's BeautifulSoup library.

### Annotations
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
Each text in the dataset was tokenized and counted afterwards.

#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
Tokenization was done using Tiktoken's encoding `cl100k_base`, used by `gpt-4-turbo`, `gpt-4`, `gpt-3.5-turbo`, etc.

#### Personal and Sensitive Information
This data does not contain ant personal, sensitive or private information.

## Dataset Card Authors

Zeynep Cahan

## Dataset Card Contact

zeynepcahan8@gmail.com