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Recent improvements in the accessibility of high-throughput genotyping have brought a great deal of attention to disease association and susceptibility studies. This paper explores possibility of applying combinatorial methods to disease susceptibility prediction. The proposed combinatorial methods as well as standard statistical methods are applied to publicly available genotype data on Crohn's disease...
The objective of this study was to simulate clamping of the aorta. It is computationally demanding and involves contact between clamp and aorta, large deformations, and fluid-structure interactions (FSI). Models of the aortic root and clamp were created and solve in ADINA, a finite element analysis package. The tissue model was created using a non-linear material. Fluid-structure interactions (FSI)...
Designing and developing computer-based self-care tools faces challenges for modeling self-care decision making processes and monitoring self-care activities. In this paper, a simplified conceptual model for self-care decision making is presented and a workflow based self-care management system is proposed to implement the process-oriented monitoring. Self-care knowledge of specific conditions is...
This paper presents the research in developing data mining ensembles for predicting the risk of osteoporosis prevalence in women. Osteoporosis is a bone disease that commonly occurs among postmenopausal women and no effective treatments are available at the moment, except prevention, which requires early diagnosis. However, early detection of the disease is very difficult. This research aims to devise...
Biological markers are useful tools for the diagnosis and prognosis of disease. Many different methods are currently used to extract markers from multiple data sources, including gene expression microarrays. This paper investigates the effect of outlier removal on the performance of one such biomarker selection method, support vector machines (SVM). A simple method of outlier removal is employed as...
Many prediction studies of medical research lead to discrete longitudinal data with repeated measurement and categorical outcomes. Therefore the traditional likelihood-based methods for continuous outcome measures are no longer suitable. With the development of modern computing technologies and improved scope for estimation via iterative sampling methods, Bayesian analysis is becoming increasingly...
Based on the analogy between the B-spline curve modeling and the force-deflection behavior of a beam subjected to lateral point loads, an extension to the B-spline surface modeling method was introduced. The proposed method has strong extrapolating capability and can develop accurate surface models over an incomplete net of data points without affecting the original data. Extrapolation of the incomplete...
We analyse the clinical process of patient referral developed and in routine use for over 5 year at Chorleywood Health Centre, UK. The system combines diagnostics performed in primary care with results forwarded to the consultant in electronic form. Patients may then be referred for teleconsultation between patient and local health care professional and distant consultant. By ensuring diagnostic information...
This paper presents a novel soft computing system for differential diagnosis of the dysarthrias and apraxia of speech based on well accepted dysarthrias' classification system used by speech and language pathologists. The dysarthrias and apraxia are complex disorders of speech because they represent a variety of neurological disturbances that can potentially affect every component of speech production...
Support vector machine (SVM) is a new learning technique based on statistical learning theory (SLT). In this paper, a medical diagnosis decision system (MDDSS) based on SVM has been established to intellectively diagnose 4 types of acid-base disturbance. SVM was originally developed for two-class classification. It is extended to solve multi-class classification problem named hierarchical SVM with...
Hereditary non-polyposis colorectal cancer (HN-PCC) is one of the most common autosomal dominant diseases in developed countries. Here, we report on a system to identify the risk of a family having HNPCC based on its history. This is important since population-wide genetic screening for HNPCC is not currently considered feasible due to its complexity and expense. If the risk of a family having HNPCC...
This paper presents the development of a decision aid tool based on a fuzzy classifier. The goal was to obtain a system that could support a physician who have to make decisions about how to deal with the progression of the disease of a child affected by Duchenne muscular dystrophy. First, we used an outranking multicriteria method to select among the possible parameters of muscle fatigue evaluation...
The purpose of this paper is to investigate the auditory discrimination skill of Malay children using computer-based method. Currently, most of the auditory discrimination assessments are conducted manually by speech-language pathologist. These conventional tests are actually general tests of sound discrimination, which do not reflect the client's specific speech sound errors. Thus, we propose computer-based...
Sleep apnea syndrome (SAS) is a very common sleep disorder disease. Reliable detection of apnea is very crucial for subsequent treatment. In this article, a novel method based on artificial neural network is proposed for such purpose. With its time-invariant property the time delay neural network (TDNN) is adopted in this system to employ the temporal trend of apnea event. As airflow and SaO take...
The clinical application shows that it is possible to differentiate between patients suffering from schizophrenia, depression and normal healthy persons on the basis of EEG rhythms. This paper describes the application of two artificial neural networks (ANN) approaches, BP ANN and self-organizing competitive ANN for the discrimination of three kinds of subjects (including 10 normal control, 10 schizophrenic...
To compare large numbers of genomic sequences of related virus, such as HIV, biologists have an increasing need for a method that can efficiently handle hundreds, even thousands, of genomic sequences accurately enough to correctly align these conserved features. In this paper, we introduce a new and efficient tool named SMA that can easily accommodate large-scale virus genomic sequences. A high-throughput...
A visualization and steering application, GAVis, has been developed to aid in understanding the behavior of and guiding the convergence of genetic algorithms running in parallel over long time periods. When classification techniques such as support vector machines (SVMs) paired with complete leave-one-out validation are used as a fitness function for identification of markers in -omic data, the time...
Despite the widespread adoption of automated perimetry, there is still a role for peripheral perimetry. So far there was no accurate quantitative analysis on the change of visual field, most analysis were qualitative and depend on doctor's experience. Computer aided diagnose system was designed to judge the accurate change in visual field. Tabu search technology was used to identify visual field from...
Inspiring product is a kind of product that enhances the existing product with a close-loop system to detect the user's health and to inspire the body in a beneficial way. The bio-signals of the users are being measured and the body is stimulated while the traditional functions of the product are used. An inspiring computer mouse prototype is specialized in this paper as an example of inspiring product...
Most current patient monitors can connect to a local area network. This has resulted in an exponential increase in the data volume to be stored, transmitted and viewed. A novel Web-based wavelet application to perform reliable display of long-term one dimensional (ID) physiological data with infrequent short duration events on the client through lossless transfer of only the useful data is proposed...
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