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嗅出真相:使用电子鼻进行临床诊断

Sniffing out the truth: clinical diagnosis using the electronic nose.

作者信息

Pavlou A K, Turner A P

机构信息

Postgraduate Medical School, Cranfield University, Bedford, UK.

出版信息

Clin Chem Lab Med. 2000 Feb;38(2):99-112. doi: 10.1515/CCLM.2000.016.

Abstract

Recently the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence (AI). It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage. Later chromatographic techniques identified an enormous number of volatiles in human clinical specimens that might serve as potential disease markers. "Artificial nose" technology has been employed in several areas of medical diagnosis, including rapid detection of tuberculosis (TB), Helicobacter pylori (HP) and urinary tract infections (UTI). Preliminary results have demonstrated the possibility of identifying and characterising microbial pathogens in clinical specimens. A hybrid intelligent model of four interdependent "tools", odour generation "kits", rapid volatile delivery and recovery systems, consistent low drift sensor performance and a hybrid intelligent system of parallel neural networks (NN) and expert systems, have been applied in gastric, pulmonary and urine diagnosis. Initial clinical tests have shown that it may be possible in the near future to use electronic nose technology not only for the rapid detection of diseases such as peptic ulceration, UTI, and TB but also for the continuous dynamic monitoring of disease stages. Major advances in information and gas sensor technology could enhance the diagnostic power of future bio-electronic noses and facilitate global surveillance models of disease control and management.

摘要

近年来,由于气味传感技术和人工智能(AI)取得了重大进展,嗅觉在临床诊断中的应用得以重新发现。过去人们就已经知道,许多感染性或代谢性疾病会释放出特定的、具有疾病阶段特征的气味。后来,色谱技术在人类临床标本中鉴定出大量挥发性物质,这些物质可能作为潜在的疾病标志物。“人工鼻”技术已应用于医学诊断的多个领域,包括结核病(TB)、幽门螺杆菌(HP)和尿路感染(UTI)的快速检测。初步结果表明,在临床标本中识别和鉴定微生物病原体是有可能的。一种由四个相互依存的“工具”组成的混合智能模型,即气味生成“试剂盒”、快速挥发性物质输送和回收系统、稳定的低漂移传感器性能以及并行神经网络(NN)和专家系统的混合智能系统,已应用于胃部、肺部和尿液诊断。初步临床试验表明,在不久的将来,不仅有可能使用电子鼻技术快速检测消化性溃疡、尿路感染和结核病等疾病,还能对疾病阶段进行连续动态监测。信息和气体传感器技术的重大进展可能会提高未来生物电子鼻的诊断能力,并促进疾病控制和管理的全球监测模式。

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