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This paper describes the development of a novel content-based image retrieval system using Multiple-Instance Learning (MIL). MIL is designed for learning on bags, each composed of a number of instances (i.e., feature vectors). For a given bag, one or more instances may be responsible for the observed classification of the bag, but their identities are unknown. What we can observe is only the label...
Discovering human disease-causing genes (disease genes in short) is one of the most challenging problems in bioinformatics and biomedicine, as most diseases are related in some way to our genes. Various methods have been proposed to exploit existing data sources for solving the problem. We aim to develop a novel method to predict disease genes that takes into account the imbalance between known disease...
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