Emergency Medicine, Disease Surveillance, and Informatics

紧急医疗系统(EMS)机构作为医疗紧急情况下的第一反应者，在为监测和早期预警系统提供有价值的数据方面具有独特的地位。在大多数州，所有进入EMS的患者都使用院前护理报告从他们的院前护理跟踪到急诊室。聚合酶链式反应用于收集重要的患者信息，卫生保健管理人员使用这些信息作为资源，通过宏观分析确定趋势。目前，PCR数据大多以纸质表格形式存在，将这些数据输入可处理和挖掘信息的数据库的过程可能需要长达数年的时间，因为没有自动手段从医院提取这些数据并将其传输到中央位置进行整理和分析。本研究的目的是通过对文档图像的理解和笔迹分析来弥补这一不足。智能价值研究团队致力于从布局结构松散的医疗表格中提取和识别手写文本数据的解决方案，这些表格具有松散的布局结构、大量的医疗词汇表以及大量的缩写和非标准书写风格。如果成功，这项工作将推进手写识别领域的最先进水平，仅限于使用不到1000个单词的小型原始词汇的应用程序。拟议的从扫描的表格中识别PCR数据的机器任务需要识别数万个单词的词汇表，这也必须考虑到非标准缩写和医学术语。这种情况下的研究挑战将是使用来自表单上可以准确和高效识别的字段的提示，例如复选框数据，以限制叙述性字段中单词的词汇大小。更广泛的影响尽管围绕防范可能的生物恐怖袭击的准备问题进行了宣传，但没有提出许多短期到中期的实用技术解决办法来解决这一问题。拟议的项目将大大提高收集聚合酶链式反应数据以填充国家EMS数据库的速度，从而为紧急医疗服务提供者和卫生保健管理人员提供丰富的数据，这些数据可用于趋势分析，以及早发现疾病暴发，并分配公共资源用于紧急服务。

Emergency Medical Systems (EMS) agencies, as first responders in medical emergency scenarios, are uniquely positioned to provide valuable data for surveillance and early warning systems. In most states, all patients who enter the EMS are tracked through their pre-hospital care to the emergency room using the Pre-Hospital Care Report. The PCR is used to gather vital patient information that is used by health care administrators as a resource to identify trends through macro analysis. Currently, the PCR data exists mostly on paper forms and the process of keying this data into a database that can be processed and mined for information can take up to several years as there is no automated means to extract this data from hospitals and transmit them to a central location for collating and analysis. The goal of this research is to attach this deficiency by using document image understanding and handwriting analysis. Intellectual Merit The research team work toward solutions to extraction and recognition of handwritten text data from medical forms with loosely constrained layout structure, large medical vocabulary, and abundance of abbreviations and non-standard writing styles. If successful, this work will advance the state-of-the-art in handwriting recognition limited to applications with small 'pristine' vocabularies of less than a thousand words. The proposed task of machine recognition of PCR data from scanned forms requires recognition with vocabularies of tens of thousands of words which must also allow for non-standard abbreviations and medical jargon. The research challenge in this case will be to use cues from fields on the form that can be recognized accurately and efficiently, such as check box data, to constrain the size of the vocabulary of the words in the narrative fields. Broader Impact Despite the publicity surrounding the issue of preparedness to guard against possible bioterrorist attacks, there have not been many short to middle-term practical technological solutions proposed to address the problem. The proposed project will greatly improve the speed of collecting PCR data to populate a national EMS database, thereby providing emergency medical service providers and health care administrators a wealth of data that can be used in trend analysis for the early detection of outbreak of diseases as well as allocation of public resources for emergency services.