Most of the clinical narratives are free-text forms. The information extractions from clinical narrative text are more complicated than those from other biomedical texts, such as books, articles, literature abstracts, and so on. In this paper, we review recent published researches on the implication and technology of information extraction from free-text clinical narratives. We mainly introduce...

Changes in stock price will be influenced by many aspects of factors. When we are predicting stock price, it is difficult to build a determined mathematical model between stock prices and these complex factors. This paper first utilizes ε − SVM (ε − support vector machine) to build a stock price prediction model. By fitting the prediction error sequence, we find the law factors, which the predi...

New approaches to speaker and background model training have given rise to many recent developments in speaker recognition. Recently, various text-dependent approaches have surfaced, including a keyword Hidden Markov Models (HMM) approach [1]. This approach also deviates from the traditional bag-offrames approach by taking into account relationships in time among acoustic features for different...

To segment a image with strongly varying object sizes results generally in under-segmentation of small structures or over-segmentation of big ones, which consequences poor classification accuracies. A strategy to produce multiple segmentations of one image and classification with support vector machines (SVM) of this segmentation stack afterwards is shown.

We rederive a form of Joachims’ ξα method for tuning Support Vector Machines by the same approach as was used to derive the GACV, and show how the two methods are related. We generalize the ξα method to the nonstandard case of nonrepresentative training set and unequal misclassification costs and compare the result to the GACV estimate for the standard and nonstandard cases.