Results 1 - 10 of 63

Predicting Disease Risk Using Bootstrap Ranking and Classification Algorithms

by Ohad Manor, Eran Segal , 2013
"... Genome-wide association studies (GWAS) are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a ‘‘black box’ ’ in order to promote changes in life ..."
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Genome-wide association studies (GWAS) are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a ‘‘black box’ ’ in order to promote changes

Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction

by Jyoti Soni, Ujma Ansari, Dipesh Sharma, Sunita Soni
"... The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The healthcare environment is still „information rich ‟ but „knowledge poor‟. There ..."
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that are in use in today‟s medical research particularly in Heart Disease Prediction. Number of experiment has been conducted to compare the performance of predictive data mining technique on the same dataset and the outcome reveals that Decision Tree outperforms and some time Bayesian classification is having

SVM BASED DECISION SUPPORT SYSTEM FOR HEART DISEASE CLASSIFICATION WITH INTEGER-CODED GENETIC ALGORITHM TO SELECT CRITICAL FEATURES

by Sumit Bhatia, Praveen Prakash, G. N. Pillai
"... The paper presents a decision support system for heart diseases classification based on support vector machines (SVM) and integer-coded genetic algorithm (GA). Simple Support Vector Machine (SSVM) algorithm has been used to determine the support vectors in a fast, iterative manner. For selecting the ..."
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The paper presents a decision support system for heart diseases classification based on support vector machines (SVM) and integer-coded genetic algorithm (GA). Simple Support Vector Machine (SSVM) algorithm has been used to determine the support vectors in a fast, iterative manner. For selecting

Disease Classification with Integer-Coded Genetic Algorithm to Select Critical Features

by Sumit Bhatia, Praveen Prakash, G. N. Pillai
"... Abstract—This paper presents a decision support system for heart disease classification based on support vector machine (SVM) and integer-coded genetic algorithm (GA). Simple Support Vector Machine (SSVM) algorithm has been used to determine the support vectors in a fast, iterative manner. For selec ..."
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Abstract—This paper presents a decision support system for heart disease classification based on support vector machine (SVM) and integer-coded genetic algorithm (GA). Simple Support Vector Machine (SSVM) algorithm has been used to determine the support vectors in a fast, iterative manner

Prediction of Financial Performance Using Genetic Algorithm and Associative Rule Mining

by Shruti Samant
"... Abstract — The proposed system introduces a new genetic algorithm for prediction of financial performance with input data sets from a financial domain. The goal is to produce a GA-based methodology for prediction of stock market performance along with an associative classifier from numerical data. T ..."
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Abstract — The proposed system introduces a new genetic algorithm for prediction of financial performance with input data sets from a financial domain. The goal is to produce a GA-based methodology for prediction of stock market performance along with an associative classifier from numerical data

Optimization of Association Rule Mining using Improved Genetic Algorithms*

by Manish Saggar
"... Abstract: In this paper, the main area of concentration was to optimize the rules generated by Association Rule Mining (apriori method), using Genetic Algorithms. In general the rule generated by Association Rule Mining technique do not consider the negative occurrences of attributes in them, but by ..."
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, but by using Genetic Algorithms (GAs) over these rules the system can predict the rules which contains negative attributes. The main motivation for using GAs in the discovery of high-level prediction rules is that they perform a global search and cope better with attribute interaction than the greedy rule

Classification method for prediction of multifactorial disease development using interaction between genetic and environmental factors, IEEE computational systems bioinformatics conference, abstract

by Yasuyuki Tomita, Mitsuhiro Yokota, Hiroyuki Honda , 2005
"... Recently, genetic linkage and association studies have already identified several candidate genes that may predispose to MI [1]. Thus genetic factors may be necessary for development of the disease, but the disease would not be manifested without the presence of an environmental risk factor [1]. The ..."
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Recently, genetic linkage and association studies have already identified several candidate genes that may predispose to MI [1]. Thus genetic factors may be necessary for development of the disease, but the disease would not be manifested without the presence of an environmental risk factor [1

A Case Study on Medical Diagnosis of Cardiovascular Diseases Using a Genetic Algorithm for Tuning Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets

by J. Sanz, M. Pagola, H. Bustince, A. Brugos, A. Fernández, F. Herrera
"... Abstract—In this contribution, we use Fuzzy Rule-Based Classification Systems for classifying the patients with respect to the risk of suffering cardiovascular diseases. Specifically, we use a methodology in which the linguistic labels of the classifier are modeled by means of IVFSs. Thereafter, the ..."
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Abstract—In this contribution, we use Fuzzy Rule-Based Classification Systems for classifying the patients with respect to the risk of suffering cardiovascular diseases. Specifically, we use a methodology in which the linguistic labels of the classifier are modeled by means of IVFSs. Thereafter

COST EFFECTIVE APPROACH ON FEATURE SELECTION USING GENETIC ALGORITHMS AND FUZZY LOGIC FOR DIABETES DIAGNOSIS.

by E. P. Ephzibah
"... A way to enhance the performance of a model that combines genetic algorithms and fuzzy logic for feature selection and classification is proposed. Early diagnosis of any disease with less cost is preferable. Diabetes is one such disease. Diabetes has become the fourth leading cause of death in devel ..."
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A way to enhance the performance of a model that combines genetic algorithms and fuzzy logic for feature selection and classification is proposed. Early diagnosis of any disease with less cost is preferable. Diabetes is one such disease. Diabetes has become the fourth leading cause of death

Neural Network Prediction in a System for Optimizing Simulations

by Manuel Laguna, Rafael Martí - IIE Transaction on Operations Engineering , 2000
"... Abstract — Neural networks have been widely used for both prediction and classification. Backpropagation is commonly used for training neural networks, although the limitations associated with this technique are well documented. Global search techniques such as simulated annealing, genetic algorithm ..."
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Abstract — Neural networks have been widely used for both prediction and classification. Backpropagation is commonly used for training neural networks, although the limitations associated with this technique are well documented. Global search techniques such as simulated annealing, genetic
Results 1 - 10 of 63