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In addition to the sparse user-item (U-I) matrix, an increasing number of current recommender systems seek to improve performance by exploiting extra heterogeneous data sources (e.g., online social networks). Such rich side sources can provide very useful information about users' personal behaviors and items' properties, therefore can significantly benefit recommender systems. Most existing work can...
One of the main goals of genome wide association studies (GWAS) has been detecting gene-gene interactions, also known as epistasis in a broad sense, underlying complex diseases. However, high dimensionalities of genotype data and exponential complexity of the search space with respect to the order of targeted interactions make most of existing interaction detection strategies practically inapplicable...
Structural variation (SV) has been reported to be associated with numerous diseases such as cancer. With the advent of next generation sequencing (NGS) technologies, various types of SV can be potentially identified. We propose a model based clustering approach utilizing a set of features defined for each type of SV event. Our method, termed SVMiner, not only provides a probability score for each...
By introducing status and progress of data mining and analyzing characteristics of medical data, a mathematical model of clinical medicine data mining is designed using data preprocessing, artificial neural network and manifold learning, focusing on data mining of clinical biochemical examining results for high-risk population with cancer and cardiovascular disease, and taking model output whose input...
With the rapid development of high-throughput genotyping technologies, more and more attentions are paid to the disease association study identifying DNA variations that are highly associated with a specific disease. One main challenge for this study is to find the optimal subsets of Single Nucleotide Polymorphisms (SNPs) which are most tightly associated with diseases. Feature selection has become...
Nowadays, the lung lobe segmentation is the most basic step in Lung CAD (Computer-aided diagnosis) and is playing an increasingly important role in the early diagnosis of lung diseases and the analysis of pulmonary functions. The key to achieving lung lobe segmentation is to detect and locate lung fissures. With the wide applications of HRCT (High-Resolution Computed Tomography), CT data with higher...
Objective: The outbreak of animal infectious diseases directly affects the economic benefits of livestock and poultry production, and even threatens the safety of human life. And due to the specificity of livestock and poultry production, the infectious diseases will be difficult to control by medical treatment means when outbreak in groups. Knowing the outbreak and development of infectious diseases...
Objective: The mathematical model prediction has been widely recognized among many disease forecasting methods. But different models will show out distinct prediction results of different diseases, as well as their occurrence locations. In this study, ARMA, exponential smoothing and seasonal index model were adopted for predicting incidence of Newcastle disease, and evaluating the precision of these...
The capsule endoscope technology has been successfully utilized to diagnose diseases of the small intestine and it has proved to greatly alleviate the discomfort and pain of the patients. In this paper we introduced several compression algorithms for capsule endoscope images. These compression algorithms are equipped with the 4times4 integer unitary transform and need no multiplication. Some new compression...
Genome-wide association studies (GWAS) provide a new and powerful approach to investigate the effect of inherited genetic variation on risks of complex diseases. With recent advances in genotyping technology, genome-wide association studies are now becoming a reality. Within the past two years, scientists have successfully replicated genetic risks of several complex diseases including cancers, obesity,...
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