The Australian E-Health Research Centre, CSIRO.
Stud Health Technol Inform. 2024 Sep 24;318:18-23. doi: 10.3233/SHTI240885.
While Fast Healthcare Interoperability Resources (FHIR) clinical terminology server enables quick and easy search and retrieval of coded medical data, it still has some drawbacks. When searching, any typographical errors, variations in word forms, or deviations in word sequence might lead to incorrect search outcomes. For retrieval, queries to the server must strictly follow the FHIR application programming interface format, which requires users to know the syntax and remember the attribute codes they wish to retrieve. To improve its functionalities, a natural language interface was built, that harnesses the capabilities of two preeminent large language models, along with other cutting-edge technologies such as speech-to-text conversion, vector semantic searching, and conversational artificial intelligence. Preliminary evaluation shows promising results in building a natural language interface for the FHIR clinical terminology system.
虽然快速医疗互操作性资源（FHIR）临床术语服务器能够快速轻松地搜索和检索编码的医疗数据，但它仍然存在一些缺点。在搜索时，任何打字错误、词形变化或词序偏差都可能导致搜索结果不正确。对于检索，对服务器的查询必须严格遵循 FHIR 应用程序编程接口格式，这要求用户了解语法并记住他们希望检索的属性代码。为了提高其功能，构建了一个自然语言接口，利用了两个卓越的大型语言模型的功能，以及其他前沿技术，如语音到文本转换、向量语义搜索和会话式人工智能。初步评估表明，为 FHIR 临床术语系统构建自然语言接口具有很有前途的结果。
