scholarly journals A Proteomic Approach for the Diagnosis of‘Oketsu’(blood stasis), a Pathophysiologic Concept of Japanese Traditional (Kampo) Medicine

2008 ◽  
Vol 5 (4) ◽  
pp. 463-474 ◽  
Author(s):  
Chinami Matsumoto ◽  
Tetsuko Kojima ◽  
Kazuo Ogawa ◽  
Satoshi Kamegai ◽  
Takuya Oyama ◽  
...  
Keyword(s):  
Decision Tree ◽  
Hierarchical Clustering ◽  
Blood Stasis ◽  
Minor Component ◽  
Principal Component ◽  
Diagnostic Algorithm ◽  
Protein Profiles ◽  
Blood Proteins ◽  
Protein Biomarkers ◽  
Proteomic Approach

‘Oketsu’is a pathophysiologic concept in Japanese traditional (Kampo) medicine, primarily denoting blood stasis/stagnant syndrome. Here we have explored plasma protein biomarkers and/or diagnostic algorithms for‘Oketsu’. Sixteen rheumatoid arthritis (RA) patients were treated withkeishibukuryogan(KBG), a representativeKampomedicine for improving‘Oketsu’. Plasma samples were diagnosed as either having an‘Oketsu’(n= 19) or ‘non-Oketsu’ (n= 29) state according to Terasawa's‘Oketsu’scoring system. Protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and hierarchical clustering and decision tree analyses were performed. KBG treatment for 4 or 12 weeks decreased the‘Oketsu’scores significantly. SELDI protein profiles gave 266 protein peaks, whose expression was significantly different between the‘Oketsu’and ‘non-Oketsu’ states. Hierarchical clustering gave three major clusters (I, II, III). The majority (68.4%) of‘Oketsu’samples were clustered into one cluster as the principal component of cluster I. The remaining‘Oketsu’profiles constituted a minor component of cluster II and were all derived from patients cured of the‘Oketsu’state at 12 weeks. Construction of the decision tree addressed the possibility of developing a diagnostic algorithm for‘Oketsu’. A reduction in measurement/pre-processing conditions (from 55 to 16) gave a similar outcome in the clustering and decision tree analyses. The present study suggests that the pathophysiologic concept ofKampomedicine‘Oketsu’has a physical basis in terms of the profile of blood proteins. It may be possible to establish a set of objective criteria for diagnosing‘Oketsu’using a combination of proteomic and bioinformatics-based classification methods.

Data Mining in Analysis of Biomechanical Signals

2009 ◽  
Vol 147-149 ◽  
pp. 588-593 ◽  
Author(s):  
Marcin Derlatka ◽  
Jolanta Pauk
Keyword(s):  
Data Mining ◽  
Principal Component Analysis ◽  
Cerebral Palsy ◽  
Spina Bifida ◽  
Decision Tree ◽  
Principal Component ◽  
Data Preprocessing ◽  
Component Analysis ◽  
Kernel Principal Component Analysis

In the paper the procedure of processing biomechanical data has been proposed. It consists of selecting proper noiseless data, preprocessing data by means of model’s identification and Kernel Principal Component Analysis and next classification using decision tree. The obtained results of classification into groups (normal and two selected pathology of gait: Spina Bifida and Cerebral Palsy) were very good.

Improving Hierarchical Clustering of Genotypic Data via Principal Component Analysis

Crop Science ◽  
2013 ◽  
Vol 53 (4) ◽  
pp. 1546-1554 ◽  
Author(s):  
T. L. Odong ◽  
J. van Heerwaarden ◽  
T. J. L. van Hintum ◽  
F. A. van Eeuwijk ◽  
J. Jansen
Keyword(s):  
Principal Component Analysis ◽  
Hierarchical Clustering ◽  
Principal Component ◽  
Component Analysis

scholarly journals New Attributes Extraction System for Arabic Autograph as Genuine and Forged through a Classification Techniques

2021 ◽  
Author(s):  
Anwar Yahya Ebrahim ◽  
Hoshang Kolivand
Keyword(s):  
Principal Component Analysis ◽  
Decision Tree ◽  
Discrete Cosine Transform ◽  
Principal Component ◽  
Component Analysis ◽  
Extraction System ◽  
Decision Tree Classifier ◽  
Tree Classifier ◽  
The World ◽  
Handwritten Recognition

The authentication of writers, handwritten autograph is widely realized throughout the world, the thorough check of the autograph is important before going to the outcome about the signer. The Arabic autograph has unique characteristics; it includes lines, and overlapping. It will be more difficult to realize higher achievement accuracy. This project attention the above difficulty by achieved selected best characteristics of Arabic autograph authentication, characterized by the number of attributes representing for each autograph. Where the objective is to differentiate if an obtain autograph is genuine, or a forgery. The planned method is based on Discrete Cosine Transform (DCT) to extract feature, then Spars Principal Component Analysis (SPCA) to selection significant attributes for Arabic autograph handwritten recognition to aid the authentication step. Finally, decision tree classifier was achieved for signature authentication. The suggested method DCT with SPCA achieves good outcomes for Arabic autograph dataset when we have verified on various techniques.

scholarly journals Decision trees in environmental justice research — a case study on the floods of 2001 and 2010 in Hungary

2019 ◽  
Vol 11 (1) ◽  
pp. 1025-1034 ◽  
Author(s):  
Gyula Nagy ◽  
György Vida ◽  
Lajos Boros ◽  
Danijela Ćirić
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Environmental Justice ◽  
Social Groups ◽  
Principal Component ◽  
Decision Making Processes ◽  
Main Factors ◽  
Decision Tree Method ◽  
Tree Method

Abstract Environmental justice is a normative framework for the analysis of environmental impacts on the wellbeing of individuals and social groups. According to the framework, the deprived social groups and ethnic minorities are often more exposed to environmental risks and hazards due to their disadvantaged situation, and due to the lack of representation and political power. To manage the impacts of injustices and to include the citizen in the decision-making processes, proper information is needed on local attitudes and decision-making processes. Therefore, this study sought to (i) identify the main factors shaping the attitudes towards environmental injustices and (ii) to analyse the attitudes and perception of the various social groups and (iii) to identify the main factors which are shaping the attitudes and actions of those who were affected by the floods of 2001 and 2010 through the use of decision tree method. The data for the predictive model was acquired from a questionnaire survey conducted in two disadvantaged and flood-hit Hungarian regions. Based on the survey data, a principal component analysis (PCA) was conducted, which resulted in three principal components; fear, social change, and change in the built environment. The study focused only on the elements of the “fear principal component”, due to the decision tree tool homogenous groups identified in relation to this component. Our analysis showed that ethnicity has a determinative role in the emergence and the level of fear from floods; the Roma respondents expressed a significantly higher level of fear than others.

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