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Heart disease classification is one of the most important topics in clinical decision support systems (CDSS). However, the performance of classification is greatly affected by feature selection. Canonical correlation analysis (CCA) is a popular method to extract effective features from two relevant data sets. In this paper, we employ discriminant minimum class locality preserving canonical correlation...
With the development of machine learning techniques, artificial intelligence applications in medicine are becoming hot topic in health information systems. In this research, we construct a new basic heart failure disease database which contains 1715 patients and 400 features. Then, we propose a new machine learning method called Polynomial Smooth Support Vector Machine(PSSVM) to help doctors diagnose...
Deep Learning, as an important branch of machine learning and neural network, is playing an increasingly important role in a number of fields like computer vision, natural language processing, etc. However, large-scale deep learning systems mainly operate in high-performance server clusters, thus restricting the application extensions to personal or mobile devices. The solution proposed in this paper...
Malware is one of the greatest and most rapidly growing threats to the digital world. Traditional signature-based detection is no longer adequate to detect new variants and highly targeted malware. Furthermore, dynamic detection is often circumvented with anti-VM and/or anti-debugger techniques. Recently heuristic approaches have been explored to enhance detection accuracy while maintaining the generality...
The issue of incomplete data exists across the entire field of data mining. In this paper, a novel two-phase method is developed to deal with the challenge of incomplete data on classification problems. In phase I, the dataset is divided into disjoint subsets based on the attributes with missing values. In phase II, each subset is used to train appropriate classification algorithms respectively in...
Alzheimer's disease (AD) is one of the most common forms of dementia and has become a serious issue among the elderly in the aging society. Since AD is incurable and degenerative, early diagnosis is essential, which can give patients and their family more opportunities to arrange their lives. In the meantime, histopathologic studies have found that MCI (mild cognitive impairment) subjects usually...
Rare class problems exist extensively in real-world applications across a wide range of domains. The extreme scarcity of the target class challenges traditional machine learning algorithms focusing on the overall classification accuracy. As a result, purposefully designed techniques are required for effectively solving the rare class mining problem. This paper presents a systematic review of the major...
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