Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

The Andalusian Public Health System Virtual Library. Four years on

The Andalusian Public Health System Virtual Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA) set up in June 2006 was determined by the II Quality Plan 2005-2008. It consists of a regional government action with the aim of democratizing the health professional access to quality scientific information, regardless of the professional workplace. Andalusia is a region with more than 8 million inhabitants, with 92,000 health professionals for 41 hospitals, 1,500 primary healthcare centres, and 10 centres for non-medical attention purposes. • To obtain documentary resources for health professionals. • To help citizens to find health information. • To coordinate the Andalusian Health Documentary centres. • To establish strategic agreements with organizations. • To contribute to the Knowledge Management Development • The BV-SSPA acquires in a centralised way, all of the information resources for the whole system. • It offers services for all professionals: o Document Supply Service o Online Learning o User service • Remote access to these resources and services. • Communication and marketing plan to promote the knowledge and use of the BV-SSPA. Presently the BV-SSPA has reached: • The subscription of 2,431 electronic reviews, 8 data bases and other scientific information resources. • The establishment of the Document Supply Service, which focuses all the article orders from and for the Andalusian Public Health System. • The starting up for the online learning platform. • The introduction of the user service and virtual reference service in beta mode. • The use of appropriate tools, as the meta-researcher and the link resolver, which allow the presentation of resources and services in a tidy, easily findable way, through a Web 2.0 page where the user can take part with his contributions and where his offers and suggestion are gathered. • Access to the resources, for the Andalusian Health Professionals worldwide requiring only an internet connection. Andalusian Health Professionals have access to the greatest Health Science Electronic Resources Collection in Spain. The BV-SSPA has become the undisputed medium for the Health Research and Clinical Healthcare in our region, being consolidated as the Knowledge Manager into the Andalusian Public Health System. In 2010, it faces new projects such as the institutional repository creation, HypatiaSalud; the analysis of our research activity; and the drafting of a normalised licence model for the contracting of electronic resources.