2005 ICSC Congress on Computational Intelligence Methods and Applications最新文献_第2页

Data mining and knowledge discovery from membrane proteins 膜蛋白的数据挖掘与知识发现

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662360

J.Y. Yang, M. Qu Yang, O. Ersoy

引用次数: 1

Holonic multi-agent system complemented by human disease ontology supporting biomedical community 以人类疾病本体为补充的全息多主体系统支持生物医学界

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662307

M. Hadzic, E. Chang

{"title":"Holonic multi-agent system complemented by human disease ontology supporting biomedical community","authors":"M. Hadzic, E. Chang","doi":"10.1109/CIMA.2005.1662307","DOIUrl":"https://doi.org/10.1109/CIMA.2005.1662307","url":null,"abstract":"The medical milieu is an open environment characterized by a variety of distributed, heterogeneous and autonomous information resources. Coordination, cooperation and exchange of information is important to the medical community. This paper presents an ontology-based holonic multi-agent system that combines the advantages of the holonic paradigm with multi-agent system technology and ontology design, in order to realize a highly reliable, adaptive, scalable, flexible and robust diagnostic system for diseases. We design a new ontology, called generic human disease ontology (GHDO), for the representation of knowledge regarding human diseases. The concepts of the GHDO ontology are organized into the following four dimensions: types, symptoms, causes and treatments of human diseases. The holonic multi-agent system uses this common GHDO ontology for purpose of query formulation, information retrieval and information integration. This intelligent dynamic system provides opportunities to collect information from multiple information resources, to share data efficiently and to integrate and manage scientific results in a timely manner. We believe such a technique is expected to become the norm once existing resources (e.g. disease databases) will have become unlocked semantically through annotation with a shared ontology","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123288954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Image fusion with perfect reconstruction DFT/RDFT filter banks and DWT 图像融合具有完美的重建DFT/RDFT滤波器组和DWT

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662324

O. Ersoy

引用次数: 0

Automatic detection of pulmonary arteries and assessment of bronchial dilatation in HRCT images of the lungs 肺动脉的自动检测和肺部HRCT图像中支气管扩张的评估

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662325

Sata Busayarat, T. Zrimec

{"title":"Automatic detection of pulmonary arteries and assessment of bronchial dilatation in HRCT images of the lungs","authors":"Sata Busayarat, T. Zrimec","doi":"10.1109/CIMA.2005.1662325","DOIUrl":"https://doi.org/10.1109/CIMA.2005.1662325","url":null,"abstract":"Bronchial dilatation is one of the most important direct signs for the diagnosis of bronchiectasis in high-resolution CT images of the lung. The assessment of the dilatation is done by comparing the size of the bronchus and accompanying artery. Previous work has shown that the success of an automatic bronchial dilatation detection method is limited by high measurement error rate of small bronchi and arteries. This paper presents a new method for automatic detection of accompanying arteries and assessment of bronchial dilatation. A knowledge-guided template matching is used to approximately locate the accompanying artery of a bronchus. A seeded region growing, with leaking prevention and correction, is used to precisely segment the artery. Bronchus-artery lumen area ratio (LAR) and their shortest diameter ratio (SDR) are used to compare the sizes of a bronchus and the accompanying artery. Machine learning is used to determine the suitable severity thresholds for different sizes of bronchi. The method was evaluated using 324 images from 64 patient studies. The results were compared with manual identification and classification, which were verified by an experienced radiologist. The method achieved 90% and 82% accuracies for artery detection and dilatation assessment, respectively","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116692413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

A, neural learning approach for tlime-varying frequency estimation of distorted harmonic signals in power systems 电力系统中畸变谐波信号时变频率估计的神经学习方法

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662367

D. Abdeslam, P. Wira, J. Mercklé, D. Flieller

引用次数: 5

The prediction of bankruptcy using fuzzy classifiers 破产预测的模糊分类器

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662315

R. Nogueira, S. Vieira, J. Sousa

引用次数: 10

Valve health monitoring with wavelet transformation and neural networks (WT-NN) 基于小波变换和神经网络的阀门健康监测

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662337

I. Tansel, J. Perotti, A. Yenilmez, P. Chen

引用次数: 3

Automated learning of genome sequences by computational intelligence 通过计算智能自动学习基因组序列

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662321

M.Q. Yang, J.Y. Yang, Zuojie Luo, O. Ersoy

{"title":"Automated learning of genome sequences by computational intelligence","authors":"M.Q. Yang, J.Y. Yang, Zuojie Luo, O. Ersoy","doi":"10.1109/CIMA.2005.1662321","DOIUrl":"https://doi.org/10.1109/CIMA.2005.1662321","url":null,"abstract":"Advent of high-throughput sequencing technology has led to an exploration of DNA sequence data available. Structures and functions of protein sequence coded for by sequenced genomes remain largely unknown. Automated identification of protein functions and interactions have been largely relying on the known 3D structures or sequence homologues. In particular, intrinsic unstructured or disordered proteins lack specific 3D structures and are unconsented during evolution, but play central roles in diseases characterized by protein misfolding and aggregation. Can we assign protein functions to sequences without relying on 3D structures, to provide useful information for the study of diseases? We developed machine learning techniques to rapidly assess protein functions from sequences. The problem of assigning functional classes to proteins is complicated by the fact that a single protein can participate in several different pathways and thus can have multiple functions (due to complex interactions among proteins). It follows that the instances in the resulting classification problem can carry multiple class labels. We have developed a tree-based classifier that capable of classifying multiply-labeled data and gained an insight into the multi-functional nature of proteins. The algorithm has been used with ensemble methods in connection with other computational intelligence to form a committee machine. Results have been compared favorably to those achieved algorithms such as decision trees and support vector machines","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127051376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hierarchical topological clustering learns stock market sectors 层次拓扑聚类学习股票市场部门

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662299

K. Doherty, R. Adams, N. Davey, W. Pensuwon

引用次数: 15

Surface EMG signals pattern recognition utilizing an adaptive crosstalk suppression preprocessor 利用自适应串扰抑制预处理的表面肌电信号模式识别

2005 ICSC Congress on Computational Intelligence Methods and Applications Pub Date : 2005-12-15 DOI: 10.1109/CIMA.2005.1662327

K. Nazarpour

引用次数: 4