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This letter shows a computer-aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) based on single photon emission computed tomography (SPECT) image feature selection and a statistical learning theory classifier. The challenge of the curse of dimensionality is addressed by reducing the large dimensionality of the input data(More)
This letter shows a computer aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The proposed method is based on partial least squares (PLS) regression model and a random forest (RF) predictor. The challenge of the curse of dimensionality(More)
This paper argues that wordnets, being concept-based computational lexica, should include information on event and argument structures. This general approach is relevant both for allowing computational grammars to cope with a number of different lexical semantics phenomena, as well as for enabling inference applications to obtain finer-grained results. We(More)
This paper examines English unbounded dependency constructions and concludes that the syntactic mechanism responsible for extraction operates in the same way in all constructions, regardless of the structures being subordinate or coordinate. In other words, this work argues that there is a general and fully uniform mechanism behind the linkage of 'gaps' and(More)
Single-photon emission tomography (SPECT) imaging has been widely used to guide clinicians in the early Alzheimer's disease (AD) diagnosis challenge. However, AD detection still relies on subjective steps carried out by clinicians, which entail in some way subjectivity to the final diagnosis. In this work, kernel principal component analysis (PCA) and(More)
This paper presents a novel method for automatic selection of regions of interest (ROIs) of functional brain images based on Gaussian mixture models (GMM), which relieves the so-called small size sample problem in the classification of functional brain images for the diagnosis of Alzheimer's disease (AD). In a first step, brain images are preprocessed in(More)
In this paper, a novel technique based on association rules (ARs) is presented in order to find relations among activated brain areas in single photon emission computed tomography (SPECT) imaging. In this sense, the aim of this work is to discover associations among attributes which characterize the perfusion patterns of normal subjects and to make use of(More)
This letter presents a novel computer-aided diagnosis (CAD) technique for the early diagnosis of Alzheimer's disease (AD) based on non-negative matrix factorization (NMF) analysis applied to single photon emission computed tomography (SPECT) images. A baseline normalized SPECT database containing normalized data for both AD patients and healthy reference(More)