Parallel workflows to personalize clinical guidelines recommendations: application to gestational diabetes mellitus

The MobiGuide system provides patients with personalized decision support tools, based on computerized clinical guidelines, in a mobile environment. The generic capabilities of the system will be demonstrated applied to the clinical domain of Gestational Diabetes (GD). This paper presents a methodology to identify personalized recommendations, obtained from the analysis of the GD guideline. We added a conceptual parallel part to the formalization of the GD guideline called "parallel workflow" that allows considering patient?s personal context and preferences. As a result of analysing the GD guideline and eliciting medical knowledge, we identified three different types of personalized advices (therapy, measurements and upcoming events) that will be implemented to perform patients? guiding at home, supported by the MobiGuide system. These results will be essential to determine the distribution of functionalities between mobile and server decision support capabilities

Spiked oscillators: exact solution

A procedure to obtain the eigenenergies and eigenfunctions of a quantum spiked oscillator is presented. The originality of the method lies in an adequate use of asymptotic expansions of Wronskians of algebraic solutions of the Schroedinger equation. The procedure is applied to three familiar examples of spiked oscillators

Automatic blood glucose classification for gestational diabetes with feature selection: decision trees vs neural networks

Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that compares 6 different feature selection methods for two machine learning algorithms: neural networks and decision trees. Three searching algorithms, Greedy, Best First and Genetic, were combined with two different evaluators, CSF and Wrapper, for the feature selection. The study has been made with 6080 blood glucose measurements from 25 patients. Decision trees with a feature set selected with the Wrapper evaluator and the Best first search algorithm obtained the best accuracy: 95.92%

A Simulation Study of an Inverse Controller for Closed and Semiclosed-Loop Control in Type 1 Diabetes

Background: Closed-loop control algorithms in diabetes aim to calculate the optimum insulin delivery to maintain the patient in a normoglycemic state, taking the blood glucose level as the algorithm's main input. The major difficulties facing these algorithms when applied subcutaneously are insulin absorption time and delays in measurement of subcutaneous glucose with respect to the blood concentration. Methods: This article presents an inverse controller (IC) obtained by inversion of an existing mathematical model and validated with synthetic patients simulated with a different model and is compared with a proportional-integral-derivative controller. Results: Simulated results are presented for a mean patient and for a population of six simulated patients. The IC performance is analyzed for both full closed-loop and semiclosed-loop control. The IC is tested when initialized with the heuristic optimal gain, and it is compared with the performance when the initial gain is deviated from the optimal one (±10%). Conclusions: The simulation results show the viability of using an IC for closed-loop diabetes control. The IC is able to achieve normoglycemia over long periods of time when the optimal gain is used (63% for the full closed-loop control, and it is increased to 96% for the semiclosed-loop control

TELMA: Entorno de formación personalizada online en Cirugía de Mínima Invasión

TELMA es un entorno de formación y aprendizaje online basado en edición de vídeo laparoscópico, la gestión del conocimiento y el trabajo colaborativo con el fin de mejorar la efectividad y eficacia de los procesos de formación (inicial y continuada) de los cirujanos de Cirugía de Mínima Invasión (CMI). TELMA explota el uso del vídeo laparoscópico como el núcleo de los contenidos didácticos y hace uso de tecnologías de formación online y gestión de contenidos digitales multimedia, para mejorar la adaptación, calidad y eficiencia del servicio ofrecido al usuario. TELMA persigue acortar las curvas de aprendizaje, proporcionando a los cirujanos un acceso ubicuo a contenidos educativos y metodologías didácticas, dotando al aprendizaje de mayor interactividad y proporcionando a los alumnos un papel más activo, una mejor adquisición de los conocimientos y habilidades y un mayor uso de las fuentes de información disponibles

Detección y seguimiento de objetos en vídeos de actividades de vida diaria para rehabilitación de pacientes con daño cerebral adquirido

Las técnicas de rehabilitación permiten la recuperación y mejora de las funciones dañadas o deterioradas y ayuda al paciente con DCA a adaptarse a su nueva situación. El avance tecnológico que se ha producido en las últimas décadas, ha impulsado la investigación en el diseño y desarrollo de nuevos modelos de rehabilitación. La tecnología de vídeo interactivo se convierte en un elemento de apoyo en estos nuevos modelos rehabilitadores. Se hace necesario desarrollar nuevos algoritmos de segmentación y seguimiento que permitan dotar de información adicional a los vídeos. En este trabajo se han implementado y evaluado dos métodos que permiten realizar la detección y el seguimiento de objetos de interés

At the beginnings of the funerary Megalithism in Iberia at Campo de Hockey necropolis

The excavations undertaken at the Campo de Hockey site in 2008 led to the identification of a major Neolithic necropolis in the former Island of San Fernando (Bay of Cádiz). This work presents the results of the latest studies, which indicate that the site stands as one of the oldest megalithic necropolises in the Iberian Peninsula. The main aim of this work is to present with precision the chronology of this necropolis through a Bayesian statistical model that confirms that the necropolis was in use from c. 4300 to 3800 cal BC. The presence of prestige grave goods in the earliest and most monumental graves suggest that the Megalithism phenomenon emerged in relation to maritime routes linked to the distribution of exotic products. We also aim to examine funerary practices in these early megalithic communities, and especially their way of life and the social reproduction system. As such, in addition to the chronological information and the Bayesian statistics, we provide the results of a comprehensive interdisciplinary study, including anthropological, archaeometric and genetic data.Archaeological background: the Campo de Hockey settlement Methods - Tomb typology - Radiocarbon dates and Bayesian analysis. - Bioarchaeology. - DNA - Grave goods Results - Tomb typology - Radiocarbon dating: Bayesian analysis - Bioarchaeology. - DNA - Grave goods. Discussion and conclusions

The Latin American Consortium of Studies in Obesity (LASO)

Current, high-quality data are needed to evaluate the health impact of the epidemic of obesity in Latin America. The Latin American Consortium of Studies of Obesity (LASO) has been established, with the objectives of (i) Accurately estimating the prevalence of obesity and its distribution by sociodemographic characteristics; (ii) Identifying ethnic, socioeconomic and behavioural determinants of obesity; (iii) Estimating the association between various anthropometric indicators or obesity and major cardiovascular risk factors and (iv) Quantifying the validity of standard definitions of the various indexes of obesity in Latin American population. To achieve these objectives, LASO makes use of individual data from existing studies. To date, the LASO consortium includes data from 11 studies from eight countries (Argentina, Chile, Colombia, Costa Rica, Dominican Republic, Peru, Puerto Rico and Venezuela), including a total of 32 462 subjects. This article describes the overall organization of LASO, the individual studies involved and the overall strategy for data analysis. LASO will foster the development of collaborative obesity research among Latin American investigators. More important, results from LASO will be instrumental to inform health policies aiming to curtail the epidemic of obesity in the region

2D-Tasks for Cognitive Rehabilitation

Neuropsychological Rehabilitation is a complex clinic process which tries to restore or compensate cognitive and behavioral disorders in people suffering from a central nervous system injury. Information and Communication Technologies (ICTs) in Biomedical Engineering play an essential role in this field, allowing improvement and expansion of present rehabilitation programs. This paper presents a set of cognitive rehabilitation 2D-Tasks for patients with Acquired Brain Injury (ABI). These tasks allow a high degree of personalization and individualization in therapies, based on the opportunities offered by new technologies