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# Dataset Card for Medical Flashcards

## Dataset Description

- **Repository:** https://github.com/kbressem/medalpaca
- **Paper:** TBA

### Dataset Summary

Medicine as a whole encompasses a wide range of subjects that medical students and graduates must master
in order to practice effectively. This includes a deep understanding of basic medical sciences, clinical knowledge,
and clinical skills. The Anki Medical Curriculum flashcards are created and updated by medical students and cover the
entirety of this curriculum, addressing subjects such as anatomy, physiology, pathology, pharmacology, and more.
These flashcards frequently feature succinct summaries and mnemonics to aid in learning and retention of vital medical concepts.

In our study, we employed the flashcards as a resource for generating question-answer pairs for training purposes.
After removing cards that contained images, we utilized OpenAI's GPT-3.5-turbo to rephrase the cards into coherent,
contextually relevant question-answer pairs. In general the questions and answers are short and focused, as the flashcards
do not allow to add much information.

### Citation Information

TBA

# 医学抽认卡数据集卡片
## 数据集说明
- **仓库地址**：https://github.com/kbressem/medalpaca
- **论文信息**：待公布（TBA）

### 数据集概述
医学作为一门综合性学科，涵盖了医学生与医学毕业生为实现高效临床实践所必须掌握的海量知识范畴，其中包括对基础医学、临床知识与临床技能的深度掌握。本数据集所用的安基（Anki）医学课程抽认卡由医学生制作并持续更新，完整覆盖上述医学课程体系，内容涵盖解剖学、生理学、病理学、药理学等多个学科领域。此类抽认卡通常配有简洁的内容摘要与助记口诀，助力学习者理解并牢记核心医学概念。

在本研究中，我们以该批抽认卡为基础素材，生成用于模型训练的问答样本对。我们首先剔除了包含图像的抽认卡，随后借助OpenAI的GPT-3.5-turbo模型将原抽认卡内容重写为逻辑连贯、符合上下文关联的问答样本对。由于原抽认卡的内容承载量有限，生成的问答样本整体简洁凝练、聚焦核心要点。

### 引用信息
待公布（TBA）