0000000000341729

AUTHOR

K. Brodda

showing 5 related works from this author

Nomogramme zur Bestimmung des intraerythrocytären Säure-Basen-Haushlts

1971

Auf Grundlage der Berechnungen von Brodda u. v. Mengden (1971) werden zwei Nomogramme vorgelegt, die die Zusammenhange der wichtigsten Saure-Basen-Parameter im Erythrocyten und deren Abhangigkeit von der O2-Sattigung wiedergeben. Nach Messung des WertetripelsP CO 2,P O 2 und pH im Blut lassen sich mit Hilfe dieser Nomogramme aktueller und Standard-Basenuberschus, aktuelles und Standard-Bicarbonat, Pufferbasen und Standard-pH im Erythrocyten ermitteln. Die zugeordneten Werte fur das Vollblut erhalt man zusatzlich bei Benutzung des zweiten Nomogramms. Vorteil dieser Nomogramme ist die rasche Erfassung des gesamten intraerythrocytaren Saure-Basen-Haushaltes, ohne das Aquilibrierung mit Gasgemi…

Gynecologymedicine.medical_specialtyPhysiologyChemistryPhysiology (medical)Clinical BiochemistrySaure basen haushaltmedicineHuman physiologyPflügers Archiv
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The Multivariate Individual Selection of Diagnostic Tests and the Reserved Diagnostic Statement: An Optimum Combination of Two New Methods for the Co…

1984

A combination of two new methods for the diagnostic procedure in computer-aided differential diagnosis is presented. It is constructed on the basis of new results of our own in the field of mathematical decision theory and is demonstrated by the differential diagnosis of congenital heart diseases by means of ECG features.

Statement (computer science)Multivariate statisticsbusiness.industryComputer scienceDecision theoryDiagnostic testMachine learningcomputer.software_genreReliability engineeringComputer-aidedArtificial intelligenceDifferential diagnosisbusinesscomputerSelection (genetic algorithm)
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A computer program suitable for analysis of choice of categories in biomedical data recognition problems.

1980

The optimum choice of categories in problems of medical data recognition is governed by the choice of categories, the selection of appropriate features, and by the choice of a loss function. Under these circumstances it is often difficult to find out the suitable classification scheme. The computer program described here serves for the design of the optimum recognition procedure. The Bayes rule is used as decision rule. A criterion for the comparison of different choice of categories is given. The program can be performed after estimation of the underlying prior probabilities and the conditional densities obtained from a training set, and before testing the decision rule with real data.

Choice setComputer programComputer sciencebusiness.industryComputersDecision theoryMedicine (miscellaneous)Decision ruleFunction (mathematics)Machine learningcomputer.software_genreClassificationBayes' theoremDecision TheoryBiomedical dataResearch DesignData miningArtificial intelligencebusinesscomputerSelection (genetic algorithm)Computer programs in biomedicine
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Changes of the ratio between myelin thickness and axon diameter in the human developing sural nerve

1978

Axon caliber and myelin sheath thickness of individual nerve fibers were evaluated in the developing human sural nerve using three different methods of measurement: 1. ocular micrometer evaluation of large fibers, 2. photographic enlargements for evaluating large numbers of nerve fibers of all sizes, and 3. electron microscopic enlargements for more precise measurements in selected nerves. The average axonal diameter doubles from 5 months gestation to about 5 years of age. Large fiber group axons increase, during the same period, by a factor of 3--3.5 with a slight decrease thereafter. The myelin thickness increases more slowly, but continuously, between 5 months gestation until the age of …

MaleAdolescentSural nervePathology and Forensic MedicineCellular and Molecular NeuroscienceMyelinSural NervemedicineHumansAxonChildElectron microscopicMyelin SheathOcular micrometerChemistryMyelin sheathsInfant NewbornInfantAnatomyAxonsMicroscopy ElectronSpinal Nervesmedicine.anatomical_structurenervous systemCaliberChild PreschoolMyelin sheathFemaleNeurology (clinical)MathematicsActa Neuropathologica
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On the Construction of Optimum Categories in Biomedical Data Recognition Problems

1979

The recognition of patterns within sets of biomedical data involves the following problems: a) Proper recording of the data to be used b) Extraction of suitable features c) Choice of categories or classes which are relevant to the medical decision task d) Estimation of the underlying distributions in the case of using parametric methods e) Choice of an adequate classification rule Whereas a lot of theories and procedures exists for most of these steps — particularly in the field of computer-aided differential diagnosis of electrocardiograms (ECG) (see [6]) — there has been only rare considerations on the problems of definition of appropriate categories.

Pattern vectorComputer sciencebusiness.industryQuadratic classifierMachine learningcomputer.software_genreField (computer science)Task (project management)Biomedical dataClassification ruleParametric methodsArtificial intelligencebusinesscomputer
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