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Biomedical subjects

E Krusińska

Publications and source records attributed to E Krusińska.

11 recordsLinked to original sources
PubMed1991

Robust trend analysis in predicting histamine provocation concentration.

Trend analysis is used to predict the histamine provocation concentration PC20 during the so-called challenge test, where increasing doses of the bronchoconstricting agent are given to a patient and the spirometric examination is subsequently performed. Classical least-squares analysis of trends as well as least absolute deviations analysis are compared. The results are interesting and promising from a statistical as well as medical point of view. The methods presented can be applied to many practical problems in medicine.

Algorithms↗
PubMed1990

Robust logistic discriminant functions in diagnosing chronic obstructive airways disease.

The paper gives a comparison of the classical logistic discriminant function, the alpha-trimmed logistic discriminant function and the L1-logistic discriminant function as used for assistance of medical diagnosis in chronic obstructive airways disease. The robustified logistic discriminant functions enable one to obtain higher rates of correctly classified individuals, especially the L1-logistic discriminant function should be recommended.

Discriminant Analysis↗
PubMed1987

Objective evaluation of degree of illness with the weighted Mahalanobis distance. A study for patients suffering from chronic obturative lung disease.

An objective evaluation of the state of patients suffering from chronic obturative lung disease is presented. This evaluation is based on the standardized weighted Mahalanobis distance between a patient and a "centre of health". The method works for both continuous and discrete features. The results of the automatic valuation were compared with the ranked physician's evaluation. This was done by the Spearman rank correlation coefficient, which was statistically significant in all computed variants.

Analysis of Variance↗
PubMedDate not supplied

Classic versus sequential diagnostic support for chronic nonspecific respiratory diseases.

The authors discuss two approaches to assisted medical diagnosis of chronic nonspecific respiratory diseases, Bayes-Fisher linear discrimination and a decision tree based on the linear discriminant functions of the individual nodes. Only the two most discriminative variables obtained for differentiation of groups at individual nodes are used for the node subclassification. They are the four linguistic variables cough, character of dyspnea, physical examination of the chest, and x-ray examination of the chest obtained by conversion of discrete features. No laboratory finding is used. The tree classifier simulates a physician's thought process. Results with multigroup linear discrimination on the same four variables for both a reclassification and a cross-validation technique were comparable to the tree-scheme outcomes. The tree classifier lends itself to simple graphic presentation, the patient being created as a point in the plane of the two most discriminative variables without the need for mathematical formulas and posterior probabilities. The classification errors that appear in the chronic bronchitis group can be easily corrected using an additional variable, smoking index.

Algorithms↗
PubMedDate not supplied

Robust multivariate methods in laboratory techniques and in assisting medical diagnosis.

The usefulness of robust multivariate methods in medical applications, for example, the indirect estimation of total lung capacity by robust regression and the assistance of medical diagnosis in obstructive airways disease using robust discriminant functions, is discussed. The results of robust methods that consist in downweighting the influence of the multivariate outliers are compared with the outcomes of classical procedures. The advantages of modern robust algorithms are proved in the present study. It is planned to include the methods in the system for the computerized consulting unit for respiratory diseases that is being set up in Wrocław.

Algorithms↗