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--- |
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license: apache-2.0 |
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language: |
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- tr |
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task_categories: |
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- question-answering |
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- text-classification |
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- text-generation |
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- text-retrieval |
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tags: |
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- medical |
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- text |
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size_categories: |
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- n<1K |
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dataset_info: |
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features: |
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- name: category |
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dtype: string |
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- name: topic |
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dtype: string |
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- name: text |
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dtype: string |
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- name: num_tokens |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 14981996 |
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num_examples: 917 |
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download_size: 5518304 |
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dataset_size: 14981996 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Card for MedData_tr-1 |
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This dataset has 917 instances and 5227389 tokens in total |
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## Dataset Details |
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### Dataset Description |
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<!-- Provide a longer summary of what this dataset is. --> |
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- **Language(s) (NLP):** Turkish |
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- **License:** APACHE 2.0 |
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### Dataset Sources |
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Memorial Health Library : https://www.memorial.com.tr/saglik-kutuphanesi |
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## Dataset Structure |
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**category** : The data was split into 3 categories |
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- Tanı ve Testler (Diagnoses and Tests) |
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- Hastalıklar (Diseases) |
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- Tedavi Yöntemleri (Treatment Methods) |
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**topic** : The topic of the text content |
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**text** : Full text |
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**num_tokens** : Token count of the full text |
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## Dataset Creation |
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### Curation Rationale |
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<!-- Motivation for the creation of this dataset. --> |
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This dataset was created to increase the Turkish medical text data in HuggingFace Datasets library. |
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### Source Data |
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> |
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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. |
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#### Data Collection and Processing |
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> |
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The contents were scraped using Python's BeautifulSoup library. |
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### Annotations |
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> |
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Each text in the dataset was tokenized and counted afterwards. |
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#### Annotation process |
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<!-- 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. --> |
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Tokenization was done using Tiktoken's encoding `cl100k_base`, used by `gpt-4-turbo`, `gpt-4`, `gpt-3.5-turbo`, etc. |
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#### Personal and Sensitive Information |
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This data does not contain ant personal, sensitive or private information. |
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## Dataset Card Authors |
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Zeynep Cahan |
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## Dataset Card Contact |
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zeynepcahan8@gmail.com |
