医学人工智能——OMAHA七巧板医学术语集数据

OMAHA七巧板医学术语集目前涵盖了疾病、症状、解剖、手术、药品、医疗器械、检验检查、影像等医学领域内容。术语集的应用可帮助实现数据互联互通，在医疗AI智能等场景的应用中发挥重要作用，如可应用于电子病历系统的临床记录、特定领域垂直数据检索、语义标注、数据分析、临床辅助决策支持等多个方面。将医学知识利用OCR识别技术整理形成结构化数据，然后利用词典、正则表达式和自定义规则等方法对数据进行清洗、标准化和去冗余，再利用机器相似度、全文检索、编辑距离等推荐方式结合人工审核进行医学知识的整理和归并，生成概念、术语以及关系，最后得到医学术语集数据。

OMAHA Tangram Medical Terminology Set currently covers medical content across multiple domains including diseases, symptoms, anatomy, surgical procedures, pharmaceuticals, medical devices, laboratory tests and imaging examinations. This terminology set facilitates data interconnection and interoperability, and plays a vital role in scenarios such as medical AI applications. It can be applied to multiple scenarios including clinical record management in electronic medical record systems, vertical data retrieval in specialized fields, semantic annotation, data analysis and clinical decision support. First, medical knowledge is organized into structured data via OCR recognition technology. Subsequently, data cleaning, standardization and deduplication are performed using methods such as dictionaries, regular expressions and custom rules. Then, medical knowledge is consolidated and merged through recommendation methods including machine similarity, full-text retrieval and edit distance, in combination with manual review, to generate concepts, terms and their corresponding relationships, ultimately forming the complete medical terminology dataset.

搜集汇总

数据集介绍

特点

该数据集由浙江数字医疗卫生技术研究院提供，包含8516条医学术语数据，涵盖疾病、症状、解剖等多个医学领域，每季度更新一次。数据集通过OCR识别技术和多种算法规则处理生成，适用于电子病历系统、临床辅助决策支持等医疗AI应用场景。