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[Computer-assisted laboratory diagnosis].

Authors: N, Matsuda;

[Computer-assisted laboratory diagnosis].

Abstract

A theory of laboratory data-based diagnosis and results of its application are reported. The diagnosis was made by linear discriminant analysis and matrix analysis, and the two diagnostic modalities were tested in healthy subjects and patients with 10 different diseases of the liver and the biliary tract. The optimal number of test items to be incorporated in the discriminant for screening was 2 to 3 in liver parenchymal diseases but tended to be 4 to 5 or more in obstructive or space-occupying diseases. A newly designed matrix discrimination was applied to this evaluation. By this method, all healthy individuals could be discriminated from patients. A mean percentage of 97.5% (92-100%) of patients with liver parenchymal diseases could be discriminated by the first 2 variables, and a mean of 86.2% (71-98%) of those with obstructive or space-occupying diseases could be discriminated by the first 3 variables. The basic architecture and function of a quantitative diagnostic system for screening of diseases of the liver and the biliary tract, which we are developing on the basis of this matrix discrimination method, are outlined with our prospects of computer-assisted laboratory diagnosis.

Related Organizations
Keywords

Biliary Tract Diseases, Liver Diseases, Humans, Diagnosis, Computer-Assisted

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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