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- W2047291236 abstract "The cycles of urinary Na, K, and Cl in six controls and in four patients with aldosterone-secreting adenoma were studied over several days of constant intake and controlled posture ( R = 24-hr recumbency; S d = erect position 0700–1900 hr). The logarithmically transformed data are analyzed by Fourier series, analysis of variance and power spectrum. Signal analysis indicates that the Fourier mean and coefficients of the 24-hr harmonic from S d are the pattern components of choice for training a Pattern Classifier. The classifier is a committee machine composed of a decision-maker for each electrolyte. The decision-makers are based upon the Ho-Kashyap algorithm for linear separability; the classification of the individual as normal or primary aldosteronism patient is given by the committee by a majority decision. The machine proved reliable and highly efficient (error rate <5%) when tested by the data from twelve normal subjects. Of two additional patients with clinical primary aldosteronism, one (adrenal adenoma at laparotomy) was correctly classified; the second one (not operated upon yet) was placed in the “no decision” region. Pattern classification, being deterministic, requires no assumption of data distribution; it may also achieve statistical significance with a sufficiently large number of training sets. Its first successful application to renal electrolyte cycles in primary aldosteronism may be expanded and upgraded by including other diseases and other methods of signal analysis and separation." @default.
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- W2047291236 date "1971-06-01" @default.
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- W2047291236 title "Pattern classification of renal electrolyte cycles in primary aldosteronism" @default.
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- W2047291236 doi "https://doi.org/10.1016/0010-4809(71)90033-4" @default.
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