---
license: cc-by-nc-sa-4.0
language:
- zh
task_categories:
- text-generation
tags:
- health
- medical
- Taiwan
- pretrain
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: token_count
    dtype: int64
  - name: word_count
    dtype: int64
  - name: url
    dtype: string
  - name: updated_at
    dtype: string
  splits:
  - name: train
    num_bytes: 138922606
    num_examples: 48627
  download_size: 138922606
  dataset_size: 138922606
configs:
- config_name: default
  data_files:
  - split: train
    path: datasets.jsonl
---
# Dataset Card for tw-health-43M

<!-- Provide a quick summary of the dataset. -->
tw-health-43M 是一個台灣健康醫療領域的繁體中文預訓練語料集，包含 48,627 篇文章，總計約 4,366 萬 tokens。涵蓋疾病衛教、醫療新聞、公共衛生政策與健康促進等內容，適用於語言模型在醫療健康領域之持續預訓練。

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->
本資料集彙整台灣健康醫療相關之文章，涵蓋內科、外科、兒科、精神科、營養、復健、傳染病防治等多元醫療主題。每篇文章附帶 token 數、字數、來源 URL 與更新日期等元資料。

- **Curated by:** [Liang Hsun Huang](https://www.linkedin.com/in/lianghsunhuang/?locale=en_US)
- **Language(s) (NLP):** Traditional Chinese
- **License:** CC BY-NC-SA 4.0

### Dataset Sources

<!-- Provide the basic links for the dataset. -->

- **Repository:** [lianghsun/tw-health-43M](https://huggingface.co/datasets/lianghsun/tw-health-43M/)

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

本資料集主要設計用於：
* 語言模型在健康醫療領域之持續預訓練（continued pretraining），提升對台灣醫療用語與衛教知識之理解；
* 建構醫療健康知識檢索系統（RAG）之語料庫；
* 訓練醫療領域之文本分類、摘要或資訊擷取模型。

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
本資料集不適用於下列用途：
* 作為醫療診斷或治療建議之依據，因內容為衛教文章，不替代專業醫療諮詢。
* 直接作為指令微調資料，因不包含問答或對話結構。
* 作為藥物資訊查詢之權威來源。

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
```jsonl
{
  "text": "同樣都難以保持注意力 「無法專心的病」ADD、ADHD有何不同？...",
  "token_count": 726,
  "word_count": 877,
  "url": "https://example.com/article/12345",
  "updated_at": "2024-11-08"
}
```

| 欄位 | 說明 |
|---|---|
| `text` | 文章全文 |
| `token_count` | 文章 token 數 |
| `word_count` | 文章字數 |
| `url` | 文章來源 URL |
| `updated_at` | 文章更新日期 |

| 統計項目 | 數值 |
|---|---|
| 文章數 | 48,627 |
| 總 tokens | ~43.66M |
| 平均 tokens/篇 | 898 |
| 平均字數/篇 | 969 |
| 資料期間 | 2024-11-08 ~ 2024-12-23 |

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

台灣醫療體系使用繁體中文，且有其特有之醫療用語、藥品名稱與健保制度相關術語。現有的醫療語料集多以簡體中文或英文為主，缺乏針對台灣醫療語境之高品質預訓練資料。本資料集提供一個聚焦於台灣醫療知識之語料集。

### Source Data

#### 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. -->

文章擷取自台灣公開之健康醫療資訊來源。每篇文章保留全文、來源 URL 與更新日期，並計算 token 數與字數。

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

文章由醫療專業人員與相關領域之編輯團隊撰寫。

### Annotations

#### Annotation process

本資料集不包含額外標註。

#### Who are the annotators?

不適用。

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
本資料集為公開發表之衛教文章，不包含個人醫療紀錄或病患隱私資訊。部分文章可能以匿名方式引用臨床案例。

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

* 資料來源集中於特定類型之健康資訊，可能無法完整代表台灣醫療知識之全貌。
* 文章內容以衛教為主，對於深度學術研究或臨床指引之覆蓋有限。
* 資料擷取期間集中於 2024 年 11–12 月，時間覆蓋較窄。
* 醫療資訊具時效性，部分內容可能隨醫學進展而過時。

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

建議使用者在醫療應用場景中，搭配最新之醫學文獻與臨床指引進行驗證，並明確標示模型輸出不構成醫療建議。

## Citation

```bibtex
@misc{tw-health-43M,
  title        = {tw-health-43M: Taiwan Health and Medical Pre-training Corpus},
  author       = {Liang Hsun Huang},
  year         = {2024},
  howpublished = {\url{https://huggingface.co/datasets/lianghsun/tw-health-43M}},
  note         = {48,627 health articles (~43.66M tokens) in Traditional Chinese for medical domain pre-training.}
}
```

## Dataset Card Authors

[Liang Hsun Huang](https://www.linkedin.com/in/lianghsunhuang/?locale=en_US)

## Dataset Card Contact

[Liang Hsun Huang](https://www.linkedin.com/in/lianghsunhuang/?locale=en_US)