Literature DB >> 3536284

The multi-state Kalman Filter in medical monitoring.

K Gordon.   

Abstract

In order to gain the best advantage from a computer database the way in which the information is displayed is vitally important. On-line statistical techniques could prove to be a great bonus to medical monitoring but have been limited by the methodology available. The Kalman Filter is one of the most powerful methods for time series analysis, and we have now shown it to be useful in a variety of settings, including the detection of kidney transplant rejection, where detection in some patients precedes that of experienced clinicians.

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Year:  1986        PMID: 3536284     DOI: 10.1016/0169-2607(86)90109-4

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  4 in total

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Authors:  R Fried; U Gather; M Imhoff
Journal:  Proc AMIA Symp       Date:  2001

2.  An approach to intelligent ischaemia monitoring.

Authors:  A Bosnjak; G Bevilacqua; G Passariello; F Mora; B Sansó; G Carrault
Journal:  Med Biol Eng Comput       Date:  1995-11       Impact factor: 2.602

3.  Single-case research designs for the clinician.

Authors:  D Aldridge
Journal:  J R Soc Med       Date:  1991-05       Impact factor: 18.000

4.  Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer's disease diagnosis and prognosis.

Authors:  Tao Yue; Xinghua Jia; Jennifer Petrosino; Leming Sun; Zhen Fan; Jesse Fine; Rebecca Davis; Scott Galster; Jeff Kuret; Douglas W Scharre; Mingjun Zhang
Journal:  Sci Adv       Date:  2017-07-28       Impact factor: 14.136

  4 in total

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