期刊文献+

肝功能检验建议性报告软件临床分析管理的优势 被引量:4

The Advantages of Clinical Analysis Management Liver Laboratory Test Proposal Report
下载PDF
导出
摘要 介绍一种方便于临床分析、鉴别诊断和分析管理的临床检验专家系统。利用人工神经网络(Artificial Neural.Networks,ANN)挖掘患者基本信息和实验室数据,进行综合统计分析,对已确诊的患者(肝炎、肝癌、肝硬化和胆囊结石)的生化检验项目进行梳理,得出相应疾病生化指标的临床阳性预测值,然后以各项生化指标为多因素变量、诊断为输出变量建立ANN预测模型。另外抽取肝功异常并已明确诊断的患者60例进行生化指标测定,利用ANN系统,综合分析预测临床符合率,同时构建对初诊病人的树状筛查程序和直观判读报告软件的开发。利用专家诊断系统对肝脏疾病预测的准确率分别为:肝炎80.0%、肝硬化86.7%、肝癌66.7%和胆囊结石73.3%,优化后的报告格式直观反映患者的病情变化。借助于建议性报告软件可快速简易地作出对肝胆系统疾病鉴别诊断,达到医疗资源优化利用的目的。 Basic information and laboratory data from patients for comprehensive statistical analysis are introduced.Based on Artificial Neural Networks(ANN),biochemical tests of definite diagnosis diseases are analyzed,such as hepatitis,hepatic carcinoma cirrhosis,cholecystolithiasis,and positive predictive value of biochemical indexes from the corresponding diseases is obtained.Finally,ANN forecasting model is established relied on multivariate variables taken from biochemical indexes and output variables taken from diagnosis.Furthermore,the predictive clinical coincidence rate of 60 patients,who are definitely diagnosed as abnormal liver function is comprehensively analyzed,and the development of tree-like screening program and visual interpretation report software is constructed.Through expert diagnosis system,the forecasting accurate rate of hepatic diseases is used as follows:hepatitis 80.0%,hepatic carcinoma 66.7%,cirrhosis 86.7%,and cholecystolithiasis 73.3%.The optimal report form directly reflects disease evolution of patients.By means of proposal report software,differential diagnosis of hepatobiliary system disease could be rapidly and simplely made,and optimal utilization of medical resources is consequently achieved.
出处 《中国医院管理》 2010年第11期49-50,共2页 Chinese Hospital Management
关键词 专家诊断系统 肝功能检验 报告软件 临床阳性率 expert diagnosis system clinical biochemical tests report software clinical positive incidence
  • 相关文献

参考文献4

二级参考文献1

共引文献7

同被引文献24

  • 1王爱民.神经网络应用于模糊综合评价的研究[J].系统工程理论与实践,1995,15(10):37-42. 被引量:48
  • 2李道伦,卢德唐,孔祥言,杜奕.BP神经网络隐式法在测井数据处理中的应用[J].石油学报,2007,28(3):105-108. 被引量:14
  • 3中华医学会肝病学分会,中华医学会感染病分会.慢性乙型肝炎防治指南:2010年版[J].肝脏,20ll,16(1):2-16.
  • 4Rockey D,Bissell D. Noninvasive measures of liver fibro- sis[J]. Hepatology, 2006,43 : S113-S120.
  • 5Imbert-Bismut F, Ratziu V, Pieroni I, et al. Biochemical mark- ers of liver fibrosis in patients with hepatitis C virus infec- tion., a prospective study [J]. Lancet, 2001, 357 : 1069- 1075.
  • 6Forns X, Amprudanes S, Love JM, et al. Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive mode [J]. Hepatology, 2002, 36: 986- 992.
  • 7Wai CT, Greenson J K, Fontana R J, et al. A simple nonin- vasive index can predict both significant fibrosis and cir- rhosis in patients with chronic hepatitis C[J]. Hepatolo- gy, 2003,38 : 518-526.
  • 8Patel K,Gordon SC,Jacobson I,et al. Evaluation of a pan- el of non-invasive serum markers to differentiate mild from moderate-to-advanced liver fibrosis in chronic hepa- titis C patients[J].Hepatology, 2004,41:935-942.
  • 9Paul Cales, Frederic Oberti, Sophie Michalak, et al. A no- vel panel of blood markers to assess the degree of liver fi- brosis[J]. Hepatology, 2005,42 :1373-1381.
  • 10方婵娟.肝硬化疾病诊断中的生化检验项目价值探讨[J].健康必读(中旬刊),2013,12(2):128.

引证文献4

二级引证文献46

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部