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An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier
P. Rajendran,M. Madheswaran +1 more
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An improved image mining technique for brain tumor classification using pruned association rule with MARI algorithm is presented in this paper and can assist the physicians for efficient classification with multiple keywords per image to improve the accuracy.Abstract:
An improved image mining technique for brain tumor classification using pruned association rule with MARI algorithm is presented in this paper. The method proposed makes use of association rule mining technique to classify the CT scan brain images into three categories namely normal, benign and malign. It combines the low level features extracted from images and high level knowledge from specialists. The developed algorithm can assist the physicians for efficient classification with multiple keywords per image to improve the accuracy. The experimental result on prediagnosed database of brain images showed 96 percent and 93 percent sensitivity and accuracy respectively.read more
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Big data analytics for preventive medicine
TL;DR: This review introduces disease prevention and its challenges followed by traditional prevention methodologies, and summarizes state-of-the-art data analytics algorithms used for classification of disease, clustering, anomalies detection, and association as well as their respective advantages, drawbacks and guidelines.
Journal ArticleDOI
Multimedia data mining: state of the art and challenges
TL;DR: A survey on the problems and solutions in Multimedia Data Mining, approached from the following angles: feature extraction, transformation and representation techniques, data mining techniques, and current multimedia data mining systems in various application domains.
Journal ArticleDOI
Wavelet statistical texture features-based segmentation and classification of brain computed tomography images
A. Padma Nanthagopal,R. Sukanesh +1 more
TL;DR: The experimental results show that the proposed SVM classifier is able to achieve high segmentation and classification accuracy effectiveness as measured by sensitivity and specificity.
Journal ArticleDOI
Applications of association rule mining in health informatics: a survey
TL;DR: It has been explored that, instead of the more efficient alternative approaches, the Apriori algorithm is still a widely used frequent itemset generation technique for application of association rule mining for health informatics.
Journal ArticleDOI
Investigating machine learning techniques for MRI-based classification of brain neoplasms.
TL;DR: A computer-assisted classification framework is developed and used for differential diagnosis of brain neoplasms based on MRI that can achieve higher accuracy than most reported studies using MRI.
References
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Book ChapterDOI
Supervised and unsupervised discretization of continuous features
TL;DR: Binning, an unsupervised discretization method, is compared to entropy-based and purity-based methods, which are supervised algorithms, and it is found that the performance of the Naive-Bayes algorithm significantly improved when features were discretized using an entropy- based method.
Association Rules Mining: A Recent Overview
TL;DR: The preliminaries of basic concepts about association rule mining are provided and the list of existing association rulemining techniques are surveyed.
Proceedings ArticleDOI
Pruning and summarizing the discovered associations
Bing Liu,Wynne Hsu,Yiming Ma +2 more
TL;DR: The technique first prunes the discovered associations to remove those insignificant associations, and then finds a special subset of the unpruned associations to form a summary of the discovered association rules, which are then called the direction setting rules.
Journal ArticleDOI
An expert system for detection of breast cancer based on association rules and neural network
Murat Karabatak,M. Cevdet Ince +1 more
TL;DR: This research demonstrated that the AR can be used for reducing the dimension of feature space and proposed AR+NN model can be use to obtain fast automatic diagnostic systems for other diseases.
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Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm
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