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Feature selection continues to grow in importance in many areas of science and engineering, as large datasets become increasingly common. In particular, bioscience and medical datasets routinely contain several thousands of features. For effective data mining in such datasets, tools are required that can reliably distinguish the most relevant features. The latter is a useful goal in itself (e.g. such...
Information management and extraction in the field of biomedical research has become a requirement with the rapid increase in the amount of data being published in this area. In this paper, a graphical model, Conditional Random Fields has been used to extract a particular gene-gene relationship called ??coexpression?? from the existing literature. First, a Conditional Random Fields based model has...
Text mining tools and algorithms are being successfully used for information extraction especially on large corpus like biomedical publications. These tools not only aid in information extraction but also in forming new theories and relationships between various fields of biomedical research. Extraction of gene-gene or gene-disease relationship is one such application. In this paper, we introduce...
The nursing care quality improvement is very important for our life. Currently, nursing-care freestyle texts (nursing-care data) are collected from many hospitals in Japan by using Web applications. The collected nursing-care data are stored into the database. To evaluate nursing-care data, we have already proposed a fuzzy classification system, a neural network based system, a support vector machine...
Microarray technology has been widely applied to search for biomarkers of diseases, diagnose diseases and analyze gene regulatory network. Abundance of expression data from microarray experiments are processed by informatics tools, such as supporting vector machines (SVM), artificial neural network (ANN), and so on. These methods achieve good results in single dataset. Nevertheless, most analyses...
There are striking disparities in the prevalence of dental disease by income. Poor children suffer twice as much dental caries as their more affluent peers, but are less likely to receive treatment. This paper presents an experimental study of the application of machine learning methods to the problem of caries prediction. For this paper a data set collected from interviews with children under five...
Thalassemia is a genetic defect that is commonly found in many parts of the world. Number of humans that are suffering from this disease is determined by screening the heterozygous population. This article investigates the thalassemia screening problem using the unconstrained functional networks classifier. The learning algorithm for this new scheme is briefly illustrated. The new intelligent system...
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