Temat: wise - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Pattern recognition approach for analysis of metabolic response to intermittent hypoxia
Autorzy:: Sokołowska, B.
Jóźwik, A.
Powiązania:: https://bibliotekanauki.pl/articles/333610.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: rozpoznawanie wzorców
zasada k-NN
przerywane niedotlenienie
metaboliczna odpowiedź
pattern recognition
k-NN rule
pair-wise classifier
intermittent hypoxia
metabolic response
Opis:: Intermittent hypoxia (IH) elicits two forms of respiratory plasticity, which are initiated during and after exposure to IH, i.e. a long-term facilitation and a progressive augmentation of respiratory motor output. IH is often used as a model of sleep apnea and/or respiratory plasticity in humans and animals. Procedures of IH are also applied in sport medicine and rehabilitation of respiratory diseases. The aim of the present paper is an analysis of a metabolic response to acute intermittent hypoxia in a rat model. The animals were placed and monitored in a whole body plethysmographic chamber. The rats were exposed to five consecutive cycles consisting of 10-min hypoxic stimulus period separated by 10-min normoxic intervals, and additionally they were monitored up to 1 h after the final hypoxic exposure. The metabolism software analyzer recorded following variables (features): metabolic rate, carbon dioxide production, oxygen consumption and respiratory quotient. The obtained results demonstrated that acute IH causes metabolic effects during and after intermittent stimuli, which may be effectively recognized by an application of the k-NN classifiers.
Źródło:: Journal of Medical Informatics & Technologies; 2010, 15; 177-183
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: A pattern recognition approach to Emery-Dreifuss muscular dystrophy (EDMD) study
Autorzy:: Sokołowska, B.
Jóźwik, A.
Niebroj-Dobosz, I. M.
Hausmanowa-Petrusewicz, I.
Powiązania:: https://bibliotekanauki.pl/articles/332948.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: pattern recognition
feature selection
pair-wise linear classifier
metalloproteinases and their tissue inhibitors
Emery-Dreifuss muscular dystrophy
rozpoznawanie obrazów
wybór funkcji
metaloproteinaza
dystrofia mięśniowa
Opis:: The algorithms of pattern recognition were used for differentiation between two forms of Emery-Dreifuss muscular dystrophy (EDMD), i.e. autosomal-dominant laminopathy (AD-EDMD) and Xlinked emerynopathy (X-EDMD). A set of some matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) in serum of EDMD patients and healthy subjects were treated as features. In concluding MMPs and TIMPs levels are helpful to identifying the EDMD patients and the disease progress.
Źródło:: Journal of Medical Informatics & Technologies; 2014, 23; 165-172
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Nonparametric methods of supervised classification
Autorzy:: Jóźwik, A.
Powiązania:: https://bibliotekanauki.pl/articles/333226.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: pattern recognition
feature selection
k-NN rules
pair-wise classifier
artificial features
linear classifier
reference set size reduction
rozpoznawanie wzorca
wybór funkcji
reguła k-NN
sztuczne cechy
klasyfikator liniowy
Opis:: Selected nonparametric methods of statistical pattern recognition are described. A part of them form modifications of the well known k-NN rule. To this group of the presented methods belong: a fuzzy k-NN rule, a pair-wise k-NN rule and a corrected k-NN rule. They can improve classification quality as compared with the standard k-NN rule. For the cases when these modifications would offer to large error rates an approach based on class areas determination is proposed. The idea of class areas can be also used for construction of the multistage classifier. A separate feature selection can be performed in each stage. The modifications of the k-NN rule and the methods based on determination class areas can be too slow in some applications, therefore algorithms for reference set reduction and condensation, for simple NN rule, are proposed. To construct fast classifiers it is worth to consider also a pair-wise linear classifiers. The presented idea can be used as in the case when the class pairs are linearly separable as well as in the contrary case.
Źródło:: Journal of Medical Informatics & Technologies; 2013, 22; 21-32
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: The pair-wise linear classifier and the k-NN rule in application to ALS progression differentiation
Autorzy:: Sokołowska, B.
Jóźwik, A.
Niebroj-Dobosz, I.
Janik, P.
Powiązania:: https://bibliotekanauki.pl/articles/333011.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: rozpoznawanie wzorców
wybór funkcji
klasyfikator liniowy
zasada k-NN
biomarkery
stwardnienie zanikowe boczne
pattern recognition
feature selection
linear classifier
k-NN rule
pair-wise classifier
biomarkers
amyotrophic lateral sclerosis
Opis:: The two kinds of classifier based on the k-NN rule, the standard and the parallel version, were used for recognition of severity of ALS disease. In case of the second classifier version, feature selection was done separately for each pair of classes. The error rate, estimated by the leave one out method, was used as a criterion as for determination the optimum values of k's as well as for feature selection. All features selected in this manner were used in the standard and in the parallel classifier based on k-NN rule. Furthermore, only for the verification purpose, the linear classifier was applied. For this kind of classifier the error rates were calculated by use the training set also as a testing one. The linear classifier was trained by the error correction algorithm with a modified stop condition. The data set concerned with the healthy subjects and patients with amyotrophic lateral sclerosis (ALS). The set of several biomarkers such as erythropoietin, matrix metalloproteinases and their tissue inhibitors measured in serum and cerebrospinal fluid (CSF) were treated as features. It was shown that CSF biomarkers were very sensitive for the ALS progress.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 20; 79-83
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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