Feasibility of a Natural Language Processing-based Dental Charting Application

描述（由申请人提供）：缺乏灵活、健壮和准确的自然语言界面是牙科临床医生直接使用基于计算机的患者记录的重大障碍。在提供病人护理时，牙医、牙医和助手在使用键盘和鼠标与计算机交互方面有障碍，主要是因为感染控制方面的考虑。本提案的目的是开发和评估一个原型牙科制图系统与语音驱动的接口，将允许牙医图表使用自然语言的牙齿状况。该系统将使用自然语言处理（NLP）从转录的牙科检查中提取与16种牙齿状况相关的关键概念。这些概念，编码使用标准化的术语，将提供一个结构化的摘要病人的初步牙科exam. The建议有两个目标：1）评估的准确性语音识别技术的临床牙科检查;和2）开发和评估NLP应用程序的映射转录文本到一个结构化的牙科图表。该提案描述了一个新的，探索性和创新性的研究项目，可以从根本上影响牙科制图的实践。该提案的预期成果包括：1）理解实时口述牙科检查的语音识别准确性; 2）基于NLP的工具，将每颗牙齿的修复和牙周状况自动绘制成结构化的牙科图表。这项开发工作将提供一个强大的基础，开发一个基于NLP的椅旁牙科图表应用程序，将自动生成一个结构化的牙科图表适合椅旁决策支持。

DESCRIPTION (provided by applicant): The absence of a flexible, robust, and accurate natural language interface is a significant barrier to the direct use of computer-based patient records by dental clinicians. While providing patient care, dentists, hygienists and assistants are handicapped in using a keyboard and mouse to interact with a computer, primarily because of infection control concerns. The objective of this proposal is to develop and evaluate a prototype dental charting system with a speech-driven interface that will allow the dentist to chart dental conditions using natural language. The system will use Natural Language Processing (NLP) to extract the key concepts associated with 16 dental conditions from transcribed dental examinations. These concepts, coded using the standardized terminologies, would provide a structured summary of a patient's initial dental exam. The proposal has two aims: 1) evaluate the accuracy of speech recognition technology for clinical dental examinations; and 2) develop and evaluate an NLP application for mapping transcribed text to a structured dental chart. This proposal describes a new, exploratory and innovative research project that could radically impact the practice of dental charting. Expected outcomes for this proposal include: 1) an understanding of the accuracy of speech recognition for real-time dictated dental exams; and 2) NLP-based tools to automatically chart restorative and periodontal conditions for each tooth into a structured dental chart. This developmental work will provide a strong foundation for developing a chairside NLP-based dental charting application that would automatically generate a structured dental chart suitable for chairside decision support.