Search Results - (( tissues classification using algorithm ) OR ( data distribution function algorithm ))
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A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data
Published 2005“…Gene Selection Plays An Important Role Prior To Tissue Classification. In This Paper, A Study On Numerous Combinations Of Gene Selection Techniques And Classification Algorithms For Classification Of Microarray Gene Expression Data Is Presented. …”
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Article -
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Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter
Published 2015“…In the classification stage, the k-NN classifier is used to classify the CT images to two different classes which are Normal Tissue (NT) and Abnormal Tissue; Centrilobular Emphysema (CLE) and Paraseptal Emphysema (PSE). …”
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Final Year Project -
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Effective gene selection techniques for classification of gene expression data
Published 2005“…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. …”
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Thesis -
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…We hope that these our results would help improve the classification of breast tissue to allow the early prediction of cancer susceptibility.…”
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Conference or Workshop Item -
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
Published 2021“…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
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Student Project -
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Hybrid of swarm intelligent algorithms in medical applications
Published 2019“…In this study, feed forward and Elman recurrent neural network (ERN) with swarm intelligent algorithms is used for the classification of the mentioned diseases. …”
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Proceeding Paper -
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Gene subset selection for lung cancer classification using a multi-objective strategy
Published 2008“…A microarray machine offers the ability to measure the expression levels of thousands of genes simultaneously. It is used to collect the infonnation from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…The four are separation, classification, sorting and rooting. In this work, the type of sample involves oil palm tissue culture (OPTC) shoots obtained from the Malaysia Palm Oil Board (MPOB) tissue culture laboratory. …”
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Thesis -
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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…It is designed to incorporate with the CAPSOCA algorithm which intended to strengthen the classification outcomes. …”
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Thesis -
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Texture Classification of lung computed tomography (CT) using local binary patterns (LBP)
Published 2015“…In this work, we proposed an LBP-based lung classification algorithm. The local binary pattern (LBP) is one of the feature extraction technique that can be used in classify the image. …”
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Final Year Project -
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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Automated classification radiograph of Periodontal bone loss using deep learning
Published 2025“…Background: Periodontitis is a common chronic inflammatory condition of the supporting tissues of the teeth that destroys the tissues and, if left untreated, results in tooth loss. …”
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Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images
Published 2017“…Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. …”
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Breast cancer histological images nuclei segmentation and optimized classification with deep learning
Published 2022“…A breast cancer multi-classification technique based on a suggested deep learning algorithm was examined to achieve the accuracy of 99.2% using a huge database of ICIAR 2018, demonstrating the method’s efficacy in offering an important weapon for breast cancer multi-classification in a medical setting. …”
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