Signal-Based Analysis of Clinical Microbiology

描述（由申请人提供）：医院感染和抗菌 抵抗运动是现代社会的一个标志，影响着数百万美国人。 每年浪费数十亿美元。及时、准确的数据分析 这对防止感染和耐药性的传播至关重要。初步 结果表明，将临床微生物学数据作为信号处理， 各种分析技术对他们有巨大的潜力，以改善 早期发现疫情和耐药性的变化， 有效的干预仍然存在。基于这些结果，这 研究旨在充分描述至少五年的历史 三家著名医院的微生物数据这将被用作培训 数据，以优化早期检测技术，通过使用遗传 使用Linux超级计算集群的遗传算法。调查将是 在为期一年的试验前后， 一个早期的原型实时监测系统，以确定影响， 一个系统有能力防止传染病的传播。 成功与否将以调查结果以及 及时发现疫情。这项研究将扩大科学 了解遗传算法、传染病监测和聚集性检测。 拟定商业应用： 医院感染和抗菌素耐药性是医院面临的巨大问题。 每家医院都有感染控制计划，每个计划都必须审查微生物学数据。 基于本文提出的研究建立的监测系统将使医疗机构能够及时发现疫情和趋势，并积极干预以防止疾病传播。

DESCRIPTION (provided by applicant): Hospital infections and antimicrobial resistance are scourges of modern society, affecting several million Americans annually and wasting billions of dollars. Timely, accurate data analysis is critical to preventing the spread of infection and resistance. Preliminary results show that treating clinical microbiology data as signals and applying various analytical techniques to them has tremendous potential to improve the detection of outbreaks and shifts in resistance early on, while the possibility for effective intervention still exists. Building on these results, this research aims to fully characterize at least five years of historical microbiology data from three prominent hospitals. This will be used as training data to optimize early detection techniques through the use of genetic algorithms (GAs) using a Linux supercomputing cluster. Surveys will be conducted of the infection control personnel before and after a one year trial of an early prototype real-time monitoring system to determine the impact such a system has on their ability to prevent the spread of infectious disease. Success will be measured by the survey results as well as by the number of outbreaks detected in a timely manner. This research will extend the scientific understanding of GAs, infectious disease surveillance, and cluster detection. PROPOSED COMMERCIAL APPLICATION: Hospital infections and antimicrobial resistance are enormous problems for hospitals. Every hospital has infection control program, and every program must review microbiology data. A surveillance system built upon the research proposed herein will enable healthcare facilities to detect outbreaks and trends in a timely manner and actively intervene to prevent the spread of disease.