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Wyszukujesz frazę "Bi-Clustering" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Texture and gene expression analysis of the MRI brain in detection of Alzheimer’s disease
Autorzy:
Bustamam, A.
Sarwinda, D.
Ardenaswari, G.
Powiązania:
https://bibliotekanauki.pl/articles/91834.pdf
Data publikacji:
2018
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
Alzheimer’s disease
MRI
Feature Extraction
Bi-Clustering
Local Binary Pattern
LBP
Opis:
Alzheimer’s disease is a type of dementia that can cause problems with human memory, thinking and behavior. This disease causes cell death and nerve tissue damage in the brain. The brain damage can be detected using brain volume, whole brain form, and genetic testing. In this research, we propose texture analysis of the brain and genomic analysis to detect Alzheimer’s disease. 3D MRI images were chosen to analyze the texture of the brain, and microarray data were chosen to analyze gene expression. We classified Alzheimer’s disease into three types: Alzheimer’s, Mild Cognitive Impairment (MCI), and Normal. In this study, texture analysis was carried out by using the Advanced Local Binary Pattern (ALBP) and the Gray Level Co-occurrence Matrix (GLCM). We also propose the bi-clustering method to analyze microarray data. The experimental results from texture analysis show that ALBP had better performance than GLCM in classification of Alzheimer’s disease. The ALBP method achieved an average value of accuracy of between 75% - 100% for binary classification of the whole brain data. Furthermore, Biclustering method with microarray data shows good performance gene expression, where this information show influence Alzheimer’s disease with total of bi-cluster is 6.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 2; 111-120
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The bi-partial version of the p-median / p-center facility location problem and some algorithmic considerations
Autorzy:
Owsinski, J. W.
Powiązania:
https://bibliotekanauki.pl/articles/384947.pdf
Data publikacji:
2014
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
facility location
p-median
p-center
clustering
bi-partial approach
Opis:
The paper introduces the bi-partial version of the well known p-median or p-center facility location problem. The bi-partial approach, developed by the author, primarily to deal with the clustering problems, is shown here to work for a problem that does not possess some of the essential properties, inherent to the bi-partial formulations. It is demonstrated that the classical objective function of the problem can be correctly interpreted in terms of the bi-partial approach, that it possesses the essential properties that are at the core of the bi-partial approach, and, finally, that the general algorithmic precepts of the bi-partial approach can also be applied to this problem. It is proposed that the use of bi-partial approach for similar problems can be beneficial from the point of view of flexibility and interpretation.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 3; 59-63
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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