795 resultados para Planning decision support systems


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BACKGROUND The majority of radiological reports are lacking a standard structure. Even within a specialized area of radiology, each report has its individual structure with regards to details and order, often containing too much of non-relevant information the referring physician is not interested in. For gathering relevant clinical key parameters in an efficient way or to support long-term therapy monitoring, structured reporting might be advantageous. OBJECTIVE Despite of new technologies in medical information systems, medical reporting is still not dynamic. To improve the quality of communication in radiology reports, a new structured reporting system was developed for abdominal aortic aneurysms (AAA), intended to enhance professional communication by providing the pertinent clinical information in a predefined standard. METHODS Actual state analysis was performed within the departments of radiology and vascular surgery by developing a Technology Acceptance Model. The SWOT (strengths, weaknesses, opportunities, and threats) analysis focused on optimization of the radiology reporting of patients with AAA. Definition of clinical parameters was achieved by interviewing experienced clinicians in radiology and vascular surgery. For evaluation, a focus group (4 radiologists) looked at the reports of 16 patients. The usability and reliability of the method was validated in a real-world test environment in the field of radiology. RESULTS A Web-based application for radiological "structured reporting" (SR) was successfully standardized for AAA. Its organization comprises three main categories: characteristics of pathology and adjacent anatomy, measurements, and additional findings. Using different graphical widgets (eg, drop-down menus) in each category facilitate predefined data entries. Measurement parameters shown in a diagram can be defined for clinical monitoring and be adducted for quick adjudications. Figures for optional use to guide and standardize the reporting are embedded. Analysis of variance shows decreased average time required with SR to obtain a radiological report compared to free-text reporting (P=.0001). Questionnaire responses confirm a high acceptance rate by the user. CONCLUSIONS The new SR system may support efficient radiological reporting for initial diagnosis and follow-up for AAA. Perceived advantages of our SR platform are ease of use, which may lead to more accurate decision support. The new system is open to communicate not only with clinical partners but also with Radiology Information and Hospital Information Systems.

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The Socio-Economic Atlas of Kenya is the first of its kind to offer high-resolution spatial depictions and analyses of data collected in the 2009 Kenya Population and Housing Census . The combination of geographic and socio-eco - nomic data enables policymakers at all levels, development experts, and other interested readers to gain a spatial understanding of dynamics affecting Kenya. Where is the informal economic sector most prominent? Which areas have adequate water and sanitation? Where is population growth being slowed effectively? How do education levels vary throughout the country? And where are poverty rates lowest? Answers to questions such as these, grouped into seven broad themes, are visually illustrated on high-resolution maps. By supplying precise information at the sub-location level and summarizing it at the county level, the atlas facilitates better planning that accounts for local contexts and needs. It is a valuable decision-support tool for government institutions at different administrative levels, educational institutions, and others. Three organizations – two in Kenya and one in Switzerland – worked together to create the atlas: the Kenya National Bureau of Statistics (KNBS), the Nanyuki-based Centre for Training and Integrated Research in ASAL Development (CETRAD), and the Centre for Development and Environment (CDE) at the University of Bern. Close cooperation between KNBS, CETRAD, and CDE maximized synergies and knowledge exchange.

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These guidelines were developed in the context of working block 3 of the DESIRE project. They address the facilitators in the 18 DESIRE study sites and support them in conducting stakeholder workshops aiming at the selection and decision on mitigation strategies to be implemented in the study site context. The decision-making process is supported by a multi-objective decision support system (MODSS) Software called 'Facilitator'.

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Ensuring sustainable use of natural resources is crucial for maintaining the basis for our livelihoods. With threats from climate change, disputes over water, biodiversity loss, competing claims on land, and migration increasing worldwide, the demands for sustainable land management (SLM) practices will only increase in the future. For years already, various national and international organizations (GOs, NGOs, donors, research institutes, etc.) have been working on alternative forms of land management. And numerous land users worldwide – especially small farmers – have been testing, adapting, and refining new and better ways of managing land. All too often, however, the resulting SLM knowledge has not been sufficiently evaluated, documented and shared. Among other things, this has often prevented valuable SLM knowledge from being channelled into evidence-based decision-making processes. Indeed, proper knowledge management is crucial for SLM to reach its full potential. Since more than 20 years, the international WOCAT network documents and promotes SLM through its global platform. As a whole, the WOCAT methodology comprises tools for documenting, evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing, analysis and use for decision support in the field, at the planning level, and in scaling up identified good practices. In early 2014, WOCAT’s growth and ongoing improvement culminated in its being officially recognized by the UNCCD as the primary recommended database for SLM best practices. Over the years, the WOCAT network confirmed that SLM helps to prevent desertification, to increase biodiversity, enhance food security and to make people less vulnerable to the effects of climate variability and change. In addi- tion, it plays an important role in mitigating climate change through improving soil organic matter and increasing vegetation cover. In-depth assessments of SLM practices from desertification sites enabled an evaluation of how SLM addresses prevalent dryland threats. The impacts mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Among others, favourable local-scale cost-benefit relationships of SLM practices play a crucial role in their adoption. An economic analysis from the WOCAT database showed that land users perceive a large majority of the technologies as having benefits that outweigh costs in the long term. The high investment costs associated with some practices may constitute a barrier to adoption, however, where appropriate, short-term support for land users can help to promote these practices. The increased global concerns on climate change, disaster risks and food security redirect attention to, and trigger more funds for SLM. To provide the necessary evidence-based rationale for investing in SLM and to reinforce expert and land users assessments of SLM impacts, more field research using inter- and transdisciplinary approaches is needed. This includes developing methods to quantify and value ecosystem services, both on-site and off-site, and assess the resilience of SLM practices, as currently aimed at within the EU FP7 projects CASCADE and RECARE.

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Background. Excess weight and obesity are at epidemic proportions in the United States and place individuals at increased risk for a variety of chronic conditions. Rates of diabetes, high blood pressure, coronary artery disease, stroke, cancer, and arthritis are all influenced by the presence of obesity. Small reductions in excess weight can produce significant positive clinical outcomes. Healthcare organizations have a vital role to play in the identification and management of obesity. Currently, healthcare providers do not adequately diagnose and manage excess weight in patients. Lack of skill, time, and knowledge are commonly cited as reasons for non-adherence to recommended standards of care. The Chronic Care Model offers an approach to healthcare organizations for chronic disease management. The model consists of six elements that work together to empower both providers and patients to have more productive interactions: the community, the health system itself, self-management support, delivery system design, decision support, and clinical information systems. The model and its elements may offer a framework through which healthcare organizations can adapt to support, educate, and empower providers and patients in the management of excess weight and obesity. Successful management of excess weight will reduce morbidity and mortality of many chronic conditions. Purpose. The purpose of this review is to synthesize existing research on the effectiveness of the Chronic Care Model and its elements as they relate to weight management and behaviors associated with maintaining a healthy weight. Methods: A narrative review of the literature between November 1998 and November 2008 was conducted. The review focused on clinical trials, systematic reviews, and reports related to the chronic care model or its elements and weight management, physical activity, nutrition, or diabetes. Fifty-nine articles are included in the review. Results. This review highlights the use of the Chronic Care Model and its elements that can result in improved quality of care and clinical outcomes related to weight management, physical activity, nutrition, and diabetes. Conclusions. Healthcare organizations can use the Chronic Care Model framework to implement changes within their systems to successfully address overweight and obesity in their patient populations. Specific recommendations for operationalizing the Chronic Care Model elements for weight management are presented.^

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Much attention has been given to treating Operation Iraqi Freedom/Operation Enduring (OIF/OEF) Veterans with posttraumatic stress disorder (PTSD). However, little attention is given to those Veterans who do not meet diagnostic criteria for PTSD but who may still benefit from intervention. Research is needed to investigate the impact of how different racial/ethnic backgrounds, different levels of social support and comorbid mental health disorders impact OIF/OEF Veterans with varying levels of PTSD. The purpose of this dissertation is to examine the association of comorbid Axis I disorders, race/ethnicity, different levels of postdeployment social support and unit support on OIF/OEF Veterans with varying levels of PTSD. Data for this dissertation were from postdeployment screenings of OIF/OEF Veterans from a large Veterans Affairs hospital in southeast Texas. To examine the study hypotheses, we conducted multinomial logistic regressions of the clinician reported data. ^ The first article examined the prevalence of subthreshold and full levels of PTSD and compared Axis I and alcohol use comorbidity rates among 1,362 OIF/OEF Veterans with varying levels of PTSD. Results suggest that OIF/OEF Veterans with subthreshold PTSD experience similar levels of psychological distress as those with full PTSD and highlight the need to provide timely and appropriate mental health services to individuals who may not meet the diagnostic criteria for full PTSD. ^ These results suggest that OIF/OEF Veterans of all race/ethnicities can benefit from strong social support systems. Postdeployment social support was found to be a protective factor against the development of PTSD among White, Black and Hispanic veterans while deployment unit support was a protective factor only among Black Veterans. The second article investigated the association between postdeployment social support and unit support with varying levels of PTSD by race/ethnicity among 1,115 OIF/OEF Veterans. ^ The results of this study can help to formulate treatment and interventions for OIF/OEF Veterans with varying levels of PTSD and social support systems.^

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Expert systems for decision support have recently been successfully introduced in road transport management. In this paper, we apply three state-of-the art ILP systems to learn how to detect traffic problems.

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The adequate combination of reduced tillage and crop rotation could increase the viability of dry land agriculture in Mediterrenean zones. Crop simulation models can support to examine various tillage-rotation combinations and explore management scenarios. The decision support system for agrotechnology transfer (DSSAT) (Hoogenboom et al., 2010) provides a suite of crop models suitable for this task. The objective of this work was to simulate the effects of two tillage systems, conventional tillage (ConvT) and no tillage (NoT), and three crop rotations, continuous cereal (CC), fallow-cereal (FallowC) and legume-cereal (LegumeC), under dry conditions, on the cereal yield, soil organic carbon (SOC) and nitrogen (SON) in a 15-year experiment, comparing these simulations with field observations.

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This paper reports on an innovative approach that aims to reduce information management costs in data-intensive and cognitively-complex biomedical environments. Recognizing the importance of prominent high-performance computing paradigms and large data processing technologies as well as collaboration support systems to remedy data-intensive issues, it adopts a hybrid approach by building on the synergy of these technologies. The proposed approach provides innovative Web-based workbenches that integrate and orchestrate a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities.

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In the mid-long-term after a nuclear accident, the contamination of drinking water sources, fish and other aquatic foodstuffs, irrigation supplies and people?s exposure during recreational activities may create considerable public concern, even though dose assessment may in certain situations indicate lesser importance than for other sources, as clearly experienced in the aftermath of past accidents. In such circumstances there are a number of available countermeasure options, ranging from specific chemical treatment of lakes to bans on fish ingestion or on the use of water for crop irrigation. The potential actions can be broadly grouped into four main categories, chemical, biological, physical and social. In some cases a combination of actions may be the optimal strategy and a decision support system (DSS) like MOIRA-PLUS can be of great help to optimise a decision. A further option is of course not to take any remedial actions, although this may also have significant socio-economic repercussions which should be adequately evaluated. MOIRA-PLUS is designed to allow for a reliable assessment of the long-term evolution of the radiological situation and of feasible alternative rehabilitation strategies, including an objective evaluation of their social, economic and ecological impacts in a rational and comprehensive manner. MOIRA-PLUS also features a decision analysis methodology, making use of multi-attribute analysis, which can take into account the preferences and needs of different types of stakeholders. The main functions and elements of the system are described summarily. Also the conclusions from end-user?s experiences with the system are discussed, including exercises involving the organizations responsible for emergency management and the affected services, as well as different local and regional stakeholders. MOIRAPLUS has proven to be a mature system, user friendly and relatively easy to set up. It can help to better decisionmaking by enabling a realistic evaluation of the complete impacts of possible recovery strategies. Also, the interaction with stakeholders has allowed identifying improvements of the system that have been recently implemented.

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Este Proyecto Fin de Grado tiene como objetivo fundamental el perfeccionamiento y puesta en explotación de un sistema de ayuda a la decisión que evalúa el desarrollo del lenguaje en niños de 0 a 6 años de edad. Este sistema está formado fundamentalmente por una aplicación diseñada y construida mediante una arquitectura de componentes de software modular y reutilizable. La aplicación será usada por los pediatras para realizar evaluaciones del desarrollo del lenguaje infantil y además por los neuropediatras, logopedas y miembros de equipos de Atención Temprana para consultar las evaluaciones y validar las decisiones propuestas por el sistema. El sistema es accesible vía web y almacena toda la información que maneja en una base de datos. Asimismo, el sistema se apoya en un modelo conceptual u ontología desarrollado previamente para inferir las decisiones adecuadas para las evaluaciones del lenguaje. El sistema incorpora las funciones de gestión de los usuarios del mismo. ABSTRACT This Grade End Project has as fundamental objective the improvement and deployment of a decision support system for evaluating children language development from 0 to 6 years of age. This system is mainly formed by an application designed and built using a modular and reusable software component architecture. The application will be used by pediatricians for evaluating children´s speech development and also by neuro-pediatricians, speech therapists and early childhood intervention team members, for consulting previous evaluations and for validating system´s proposed decision. The system is web based and stores its information in a database. Likewise, the system is supported by a conceptual model or ontology previously developed to infer the appropriate decision for language evaluation. The system also includes user management functions.

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This work introduces a web-based learning environment to facilitate learning in Project Management. The proposed web-based support system integrates methodological procedures and information systems, allowing to promote learning among geographically-dispersed students. Thus, students who are enrolled in different universities at different locations and attend their own project management courses, share a virtual experience in executing and managing projects. Specific support systems were used or developed to automatically collect information about student activities, making it possible to monitor the progress made on learning and assess learning performance as established in the defined rubric.

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This paper proposes a novel combination of artificial intelligence planning and other techniques for improving decision-making in the context of multi-step multimedia content adaptation. In particular, it describes a method that allows decision-making (selecting the adaptation to perform) in situations where third-party pluggable multimedia conversion modules are involved and the multimedia adaptation planner does not know their exact adaptation capabilities. In this approach, the multimedia adaptation planner module is only responsible for a part of the required decisions; the pluggable modules make additional decisions based on different criteria. We demonstrate that partial decision-making is not only attainable, but also introduces advantages with respect to a system in which these conversion modules are not capable of providing additional decisions. This means that transferring decisions from the multi-step multimedia adaptation planner to the pluggable conversion modules increases the flexibility of the adaptation. Moreover, by allowing conversion modules to be only partially described, the range of problems that these modules can address increases, while significantly decreasing both the description length of the adaptation capabilities and the planning decision time. Finally, we specify the conditions under which knowing the partial adaptation capabilities of a set of conversion modules will be enough to compute a proper adaptation plan.

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Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. This study was conducted to test the DSSAT (Decision Support System for Agrotechnology Transfer) modelling system in rainfed semiarid central Spain. The focus is on the combined effect of tillage system and winter cereal-based rotations (cereal/legume/fallow) on the crop yield and soil quality. The observed data come from a 16-year field experiment. The CERES and CROPGRO models, included in DSSAT v4.5, were used to simulate crop growth and yield, and DSSAT- CENTURY was used in the soil organic carbon (SOC) and soil nitrogen (SN) simulations. Genetic coefficients were calibrated using part of the observed data. Field observations showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The CERES-Barley model also reflected this trend. The model predicted higher yield in the conventional tillage (CT) than in the no tillage (NT) probably due to the higher nitrogen availability in the CT, shown in the simulations. The SOC and SN in the top layer only, were higher in NT than in CT, and decreased with depth in both simulated and observed values. These results suggest that CT-VB and CT-FB were the best combinations for the dry land conditions studied. However, CT presented lower SN and SOC content than NT. This study shows how models can be a useful tool for assessing and predicting crop growth and yield, under different management systems and under specific edapho-climatic conditions. Additional key words: CENTURY model; CERES-Barley; crop simulation models; DSSAT; sequential simula- tion; soil organic carbon.

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Reducing the gap between water-limited potential yield and actual yield in oil palm production systems through intensification is seen as an important option for sustainably increasing palm oil production. Simulation models can play an important role in quantifying water-limited potential yield, and therefore the scope for intensification, but no oil palm model exists that is both simple enough and at the same time incorporates sufficient plant physiological knowledge to be generally applicable across sites with different growing conditions. The objectives of this study therefore were to develop a model (PALMSIM) that simulates, on a monthly time step, the potential growth of oil palm as determined by solar radiation and to evaluate model performance against measured oil palm yields under optimal water and nutrient management for a range of sites across Indonesia and Malaysia. The maximum observed yield in the field matches the corresponding simulated yield for dry bunch weight with a RMSE of 1.7 Mg ha?1 year?1 against an observed yield of 18.8 Mg ha?1. Sensitivity analysis showed that PALMSIM is robust: simulated changes in yield caused by modifying the parameters by 10% are comparable to other tree crop model evaluations. While we acknowledge that, depending on the soils and climatic environment, yields may be often water limited, we suggest a relatively simple physiological approach to simulate potential yield, which can be usefully applied to high rainfall environments and is considered as a first step in developing an oil palm model that also simulates water-limited potential yield. To illustrate the application possibil- ities of the model, PALMSIM was used to create a potential yield map for Indonesia and Malaysia by sim- ulating the growth and yield at a resolution of 0.1?. This map of potential yield is considered as a first step towards a decision support tool that can identify potentially productive, but at the moment degraded sites in Indonesia and Malaysia. ?