20 resultados para Medical informatics applications
Resumo:
Presentado en la mesa redonda "Innovar en gestión de información: plataformas tecnológicas para creación de contenidos compartidos" de las XIII Jornadas Bibliotecarias de Andalucía (Granada, 5 y 6 Noviembre 2015).
Resumo:
The Internet is a fundamental part of the daily life of adolescents, they consider it as a safe and confidential source of information on health matters. The aims is to describe the experience of Spanish adolescents searching for health information on the Internet. Methods A cross-sectional study of 811 school-age adolescents in Granada was carried out. An adapted and piloted questionnaire was used which was controlled by trained personnel. Sociodemographic and health variables were included together with those concerning the conditions governing access to and use of information and communication technologies (ICT). Results 811 adolescents were surveyed (99.38% response rate), mean age was 17 years old. Of these, 88% used the Internet; 57.5% used it on a daily or weekly basis and 38.7% used it occasionally. Nearly half the sample group (55.7%) stated that they used the Internet to search for health-related information. The main problems reported in the search for e-health were the ignorance of good web pages (54.8%) and the lack of confidence or search skills (23.2%). Conclusions In conclusion, it seems plausible to claim that websites designed and managed by health services should have a predominant position among interventions specifically addressed to young people.
Resumo:
Until now, mortality atlases have been static. Most of them describe the geographical distribution of mortality using count data aggregated over time and standardized mortality rates. However, this methodology has several limitations. Count data aggregated over time produce a bias in the estimation of death rates. Moreover, this practice difficult the study of temporal changes in geographical distribution of mortality. On the other hand, using standardized mortality hamper to check differences in mortality among groups. The Interactive Mortality Atlas in Andalusia (AIMA) is an alternative to conventional static atlases. It is a dynamic Geographical Information System that allows visualizing in web-site more than 12.000 maps and 338.00 graphics related to the spatio-temporal distribution of the main death causes in Andalusia by age and sex groups from 1981. The objective of this paper is to describe the methods used for AIMA development, to show technical specifications and to present their interactivity. The system is available from the link products in www.demap.es. AIMA is the first interactive GIS that have been developed in Spain with these characteristics. Spatio-temporal Hierarchical Bayesian Models were used for statistical data analysis. The results were integrated into web-site using a PHP environment and a dynamic cartography in Flash. Thematic maps in AIMA demonstrate that the geographical distribution of mortality is dynamic, with differences among year, age and sex groups. The information nowadays provided by AIMA and the future updating will contribute to reflect on the past, the present and the future of population health in Andalusia.
Resumo:
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).
Resumo:
The endocannabinoid system (ECS) has been implicated in many physiological functions, including the regulation of appetite, food intake and energy balance, a crucial involvement in brain reward systems and a role in psychophysiological homeostasis (anxiety and stress responses). We first introduce this important regulatory system and chronicle what is known concerning the signal transduction pathways activated upon the binding of endogenous cannabinoid ligands to the Gi/0-coupled CB1 cannabinoid receptor, as well as its interactions with other hormones and neuromodulators which can modify endocannabinoid signaling in the brain. Anorexia nervosa (AN) and bulimia nervosa (BN) are severe and disabling psychiatric disorders, characterized by profound eating and weight alterations and body image disturbances. Since endocannabinoids modulate eating behavior, it is plausible that endocannabinoid genes may contribute to the biological vulnerability to these diseases. We present and discuss data suggesting an impaired endocannabinoid signaling in these eating disorders, including association of endocannabinoid components gene polymorphisms and altered CB1-receptor expression in AN and BN. Then we discuss recent findings that may provide new avenues for the identification of therapeutic strategies based on the endocannabinod system. In relation with its implications as a reward-related system, the endocannabinoid system is not only a target for cannabis but it also shows interactions with other drugs of abuse. On the other hand, there may be also a possibility to point to the ECS as a potential target for treatment of drug-abuse and addiction. Within this framework we will focus on enzymatic machinery involved in endocannabinoid inactivation (notably fatty acid amide hydrolase or FAAH) as a particularly interesting potential target. Since a deregulated endocannabinoid system may be also related to depression, anxiety and pain symptomatology accompanying drug-withdrawal states, this is an area of relevance to also explore adjuvant treatments for improving these adverse emotional reactions.