Wyniki wyszukiwania - BazTech

1

Data mining approach in diagnosis and treatment of chronic kidney disease

Turiac Andreea S., Zdrodowska Małgorzata

Acta Mechanica et Automatica

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2022

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Vol. 16, no. 3

180--188

EN

Chronic kidney disease is a general definition of kidney dysfunction that lasts more than 3 months. When chronic kidney disease is advanced, the kidneys are no longer able to cleanse the blood of toxins and harmful waste products and can no longer support the proper function of other organs. The disease can begin suddenly or develop latently over a long period of time without the presence of characteristic symptoms. The most common causes are other chronic diseases – diabetes and hypertension. Therefore, it is very important to diagnose the disease in early stages and opt for a suitable treatment - medication, diet and exercises to reduce its side effects. The purpose of this paper is to analyse and select those patient characteristics that may influence the prevalence of chronic kidney disease, as well as to extract classification rules and action rules that can be useful to medical professionals to efficiently and accurately diagnose patients with kidney chronic disease. The first step of the study was feature selection and evaluation of its effect on classification results. The study was repeated for four models – containing all available patient data, containing features identified by doctors as major factors in chronic kidney disease, and models containing features selected using Correlation Based Feature Selection and Chi-Square Test. Sequential Minimal Optimization and Multilayer Perceptron had the best performance for all four cases, with an average accuracy of 98.31% for SMO and 98.06% for Multilayer Perceptron, results that were confirmed by taking into consideration the F1-Score, for both algorithms was above 0.98. For all these models the classification rules are extracted. The final step was action rule extraction. The paper shows that appropriate data analysis allows for building models that can support doctors in diagnosing a disease and support their deci-sions on treatment. Action rules can be important guidelines for the doctors. They can reassure the doctor in his diagnosis or indicate new, previously unseen ways to cure the patient.

2

Data mining techniques as a tool in neurological disorders diagnosis

Zdrodowska M., Dardzińska A., Chorąży M., Kułakowska A.

Acta Mechanica et Automatica

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2018

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Vol. 12, no. 3

217--220

EN

Neurological disorders are diseases of the brain, spine and the nerves that connect them. There are more than 600 diseases of the nervous system, such as epilepsy, Parkinson's disease, brain tumors, and stroke as well as less familiar ones such as multiple sclerosis or frontotemporal dementia. The increasing capabilities of neurotechnologies are generating massive volumes of complex data at a rapid pace. Evaluating and diagnosing disorders of the nervous system is a complicated and complex task. Many of the same or similar symptoms happen in different combinations among the different disorders. This paper provides a survey of developed selected data mining methods in the area of neurological diseases diagnosis. This review will help experts to gain an understanding of how data mining techniques can assist them in neurological diseases diagnosis and patients treatment.

3

Podwyższone wymagania oraz zasady klasyfikacji akustycznej budynków mieszkalnych w prPN-B-02151-5

Misiewicz L.

Materiały Budowlane

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2017

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nr 8

136--137

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Rule Quality Measures Settings in Classification, Regression and Survival Rule Induction : an Empirical Approach

Wróbel Ł., Sikora M., Michalak M.

Fundamenta Informaticae

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2016

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Vol. 149, nr 4

419--449

EN

The paper presents the results of research related to the efficiency of the so-called rule quality measures which are used to evaluate the quality of rules at each stage of the rule induction. The stages of rule growing and pruning were considered along with the issue of conflict resolution which may occur during the classification. The work is the continuation of research on the efficiency of quality measures employed in sequential covering rule induction algorithm. In this paper we analyse only these quality measures (8 measures) which had been recognized as effective based on previous conducted research. The study was conducted on approximately 70 benchmark datasets related to classification, regression and survival analysis problems. In the comparisons we analyzed prognostic abilities of the induced rules as well as the complexity of the resulting rule-based data models.

5

Computer-aided analysis of data from evaluation sheets of subjects with autism spectrum disorders

Pancerz K., Derkacz A., Mich O., Gomula J.

Bio-Algorithms and Med-Systems

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2016

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Vol. 12, no. 3

109--116

EN

In this paper, we deal with the problem of the initial analysis of data from evaluation sheets of subjects with autism spectrum disorders (ASDs). In the research, we use an original evaluation sheet including questions about competencies grouped into 17 spheres. An initial analysis is focused on the data preprocessing step including the filtration of cases based on consistency factors. This approach enables us to obtain simpler classifiers in terms of their size (a number of nodes and leaves in decision trees and a number of classification rules).

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Program do indukcji i oceny reguł klasyfikacyjnych, zintegrowany z pakietem R

Malara W., Sikora M., Wróbel Ł.

Studia Informatica

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2013

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Vol. 34, nr 2B

339--352

PL

Celem artykułu jest zaprezentowanie oprogramowania umożliwiającego indukcję i ocenę reguł klasyfikacyjnych w pakiecie R. Zaimplementowany algorytm indukcji realizuje strategię generowania kolejnych pokryć zbioru treningowego. Unikalną cechą algorytmu jest to, że może on wykorzystywać różne miary jakości, sterujące procesem wzrostu i przycinania reguł. Prezentowana implementacja jest jedną z pierwszych dostępnych dla środowiska R.

EN

The primary goal of this paper is to present an R package for induction and evaluation of classification rules. The implemented rule induction algorithm employs a so-called covering strategy. A unique feature of the algorithm is the possibility of using different rule quality measures during growing and pruning of rules. The presented implementation is one of the first available for R environment.

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Application of algorithms of classification for uncertainty reduction

Shakhovska N., Medykovsky M., Stakhiv P.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

284-286

EN

The methods of construction of classification rules for elimination of equivocations are described in the paper. The algorithms for the solution of primary goals are presented.

PL

W niniejszym opracowaniu opisano metody budowy zasad klasyfikacji do eliminacji ekwiwokacji. W artykule przedstawiono algorytmy do rozwiązania podstawowych zagadnień.