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A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine
Kensaku Kawamoto, David F Lobach, Huntington F Willard, Geoffrey S Ginsburg
BMC Medical Informatics and Decision Making , 2009, DOI: 10.1186/1472-6947-9-17
Abstract: Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government.A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.Through the 1990s and into the current millennium, rapid advances in genomics and related disciplines have made it possible to envision a healthcare system in which patient care is routinely optimized through the use of information on individuals' genomes and their downstream products (i.e., transcriptomes, proteomes, and metabolomes). Genomic medicine, or the use of genomic information to optimize health and healthcare [1]
Towards an interoperable information infrastructure providing decision support for genomic medicine  [PDF]
Matthias Samwald,Holger Stenzhorn,Michel Dumontier,M. Scott Marshall,Joanne Luciano,Klaus-Peter Adlassnig
Computer Science , 2011, DOI: 10.3233/978-1-60750-806-9-165
Abstract: Genetic dispositions play a major role in individual disease risk and treatment response. Genomic medicine, in which medical decisions are refined by genetic information of particular patients, is becoming increasingly important. Here we describe our work and future visions around the creation of a distributed infrastructure for pharmacogenetic data and medical decision support, based on industry standards such as the Web Ontology Language (OWL) and the Arden Syntax.
СИСТЕМИ П ДТРИМАННЯ ПРИЙНЯТТЯ Р ШЕНЬ АВ АЦ ЙНИХ ДИСПЕТЧЕР В П Д ЧАС УПРАВЛ ННЯ ПОВ ТРЯНИМ РУХОМ Системы поддержания принятия решений авиационных диспетчеров во время управления воздушным движением Systems support decision making air traffic controllers at air traffic control  [cached]
В.П. Харченко,В.А. Лазоренко
Proceedings of National Aviation University , 2008,
Abstract: Визначено основн тенденц розвитку автоматизованих систем управл ння пов тряним рухом. Проведено анал з процесу прийняття та п дтримки р шень. Розглянуто перспективи вдосконалення систем п дтримання прийняття р шень. Определены основные тенденции развития автоматизированных систем управления воздушным движением. Проведено анализ процесса принятия и поддержки решений. Рассмотрены перспективы совершенствования систем поддержки принятия решений. Main tendentious of development of air traffic control automated systems are determined. Decision-making and decision support processes have been analyzed. Prospect of decision support systems development have been reviewed.
Systems Theoretic Techniques for Modeling, Control, and Decision Support in Complex Dynamic Systems  [PDF]
Armen Bagdasaryan
Mathematics , 2010,
Abstract: We discuss the problems of modeling, control, and decision support in complex dynamic systems from a general system theoretic point of view. The main characteristics of complex systems and of system approach to complex system study are considered. We provide an overview and analysis of known existing paradigms and methods of mathematical modeling and simulation of complex systems, which support the processes of control and decision making. Then we continue with the general dynamic modeling and simulation technique for complex hierarchical systems functioning in control loop. Architectural and structural models of computer information system intended for simulation and decision support in complex systems are presented.
Decision Support System for Selection of Suitable Mariculture Site in the Western Part of Java Sea, Indonesia  [PDF]
W. Windupranata,R. Mayerle
ITB Journal of Engineering Science , 2009,
Abstract: Mariculture (marine aquaculture) has been intensified and has created essential employment opportunities over the last two-decades in Indonesia, as well as many other countries in the world. This development has also augmented environmental concerns and questions about possible environmental impacts. Considerable amounts of nutrient waste in dissolved and particulate form were released by intensive fish faming into the environment through feed excess, soluble fish excretion and faeces production. One of the first steps to avoid the dangerous environmental impacts is careful site selection. Hence, before the implementation of fish farming mariculture activities, appropriate site conditions for culturing the species should be selected in order to minimize environmental impacts arising from the farming activities (sustainability) as well as to guarantee adequate conditions from the operational point of view (suitability). The paper focuses on the development of a Decision Support System (DSS) as a tool for the decision maker in coastal zone management and mariculture for the appropriate selection of mariculture site location. Extensive use of GIS as part of the Decision Support System was deployed in this study. The DSS is based on physical, chemical and sediment criteria as well as on data of conflicting coastal use. The GIS analysis results in a map indicating the suitable areas for the improved method of offshore cage mariculture. In this study, emphasis was placed on finfish species, however the methods and results may be employed for other species as well following some modifications. The DSS was applied for the western part of Java Sea, Indonesia. The data were acquired from direct field measurement, numerical modelling and existing information from particular agencies. Numerical modelling was used to obtain spatial and temporal distributions of hydrodynamic parameters (i.e. current velocities and water levels). The Delft3D modelling system (Delft Hydraulics, The Netherlands) was employed for this purpose. The DSS was developed under GIS application of ESRI ArcGIS using weighted overlay method. Due to lack of data, some parameters were excluded from the analysis. The results showed the adequacy of the system for supporting governmental authorities in the implementation, environmental controlling, and estimation of overall carrying capacity for environmental sustainable marine fish farming.
Decision Support System for the APS Control System  [PDF]
D. A. Dohan
Physics , 2001,
Abstract: The Advanced Photon Source is now in its fifth year of routine beam production. The EPICS-based [1] control system has entered the phase in its life cycle where new control algorithms must be implemented under increasingly stringent operational and reliability requirements. The sheer volume of the control system (~270,000 records, ~145 VME-based input-output controllers (IOCs), and ~7,000,000 lines of EPICS ASCII configuration code), presents a daunting challenge for code maintenance. The present work describes a relational database that provides an integrated view of the interacting components of the entire APS control system, including the IOC low-level logic, the physical wiring documentation, and high-level client applications. The database is extracted (booted) from the same operational CVS repository as that used to load the active IOCs. It provides site-wide decision support facilities to inspect and trace control flow and to identify client (e.g., user interface) programs involved at any selected point in the front-end logic. The relational database forms a basis for generalized documentation of global control logic and its connection with both the physical I/O and with external high-level applications.
ARCHITECTURE OF DECISION SUPPORT SYSTEMS Архитектуры систем поддержки принятия решений
Kluchko V. I.,Shumkov Y. A.,Vlasenko A. V.,Karnizian R. O.
Polythematic Online Scientific Journal of Kuban State Agrarian University , 2013,
Abstract: The article describes the architecture of decision support systems and proposes general architecture of the modern decision support systems
Analytical tools and functions of GIS in the process control and decision support of mining company
Semrád Peter
Acta Montanistica Slovaca , 2001,
Abstract: The development of computer techniques, the increase in demands for the professional and possible fastest data processing, as well as for the fluency and efficiency of information gaining, exchanging and providing has a strong influence on forming the new generation of information technologies - Geografic Information Systems (GIS) that rose in the second half of the twentieth century.Advancement in this area is still progressing and GIS gradually find the enforcement in individual fields where they play a great role in the process control and decision support. Nowadays, there are applications in mining and geology, where are used especially at processing and evaluating of mining - geological documentation, optimalization of mining and technical processes, planning, distributing and managing of mining as well as economic analysis that are important in terms of investment decisions to mining business.GIS are the systems for the effective keeping, updating, processing, analysing, modelling, simulating and presenting geographically oriented information. We can identify them as computer systems helping to solve real problems that should be normally required to solve by human expert.Well equipped GIS have graphic ability and accordingly manage descriptive (attribute) data. They are able to secure mutual connection between graphical and descriptive data and in addition to command countless number of functions that enable the execution of spatial analysis. This fact is very important in mining and geological application.There are exploited mostly geostatistical analysis (e. g. modelling of distribution valuable and harmful components of mineral resouce in a mineral deposit), surface modelling and surface model analysis (e. g. at modelling the subsidence of mining territory), different methods of creating spatial and attribute queries about database for seeking necessary data (e. g. to find all mining blocks of deposit that meet required conditions and to calculate their total quantity of reserves) and distance and network analysis (modelling protection pillars as buffer zones for operating objects above ground, time calculation for transport of mineral resource, using optimal routes combined with cost calcultion), from the analytical apparatus and functions of GIS used in the process control and decision support of mining company.Modern mining is ranked to the specific group of fields with high information intensity. Because of high financial demands of the mine processes and technologies, the basical strategy of all mining companies is the utilization of infor
Tsunami early warning and decision support  [PDF]
T. Steinmetz,U. Raape,S. Te?mann,C. Strobl
Natural Hazards and Earth System Sciences (NHESS) & Discussions (NHESSD) , 2010, DOI: 10.5194/nhess-10-1839-2010
Abstract: An innovative newly developed modular and standards based Decision Support System (DSS) is presented which forms part of the German Indonesian Tsunami Early Warning System (GITEWS). The GITEWS project stems from the effort to implement an effective and efficient Tsunami Early Warning and Mitigation System for the coast of Indonesia facing the Sunda Arc along the islands of Sumatra, Java and Bali. The geological setting along an active continental margin which is very close to densely populated areas is a particularly difficult one to cope with, because potential tsunamis' travel times are thus inherently short. National policies require an initial warning to be issued within the first five minutes after an earthquake has occurred. There is an urgent requirement for an end-to-end solution where the decision support takes the entire warning chain into account. The system of choice is based on pre-computed scenario simulations and rule-based decision support which is delivered to the decision maker through a sophisticated graphical user interface (GUI) using information fusion and fast information aggregation to create situational awareness in the shortest time possible. The system also contains risk and vulnerability information which was designed with the far end of the warning chain in mind – it enables the decision maker to base his acceptance (or refusal) of the supported decision also on regionally differentiated risk and vulnerability information (see Strunz et al., 2010). While the system strives to provide a warning as quickly as possible, it is not in its proper responsibility to send and disseminate the warning to the recipients. The DSS only broadcasts its messages to a dissemination system (and possibly any other dissemination system) which is operated under the responsibility of BMKG – the meteorological, climatological and geophysical service of Indonesia – which also hosts the tsunami early warning center. The system is to be seen as one step towards the development of a "system of systems" enabling all countries around the Indian Ocean to have such early warning systems in place. It is within the responsibility of the UNESCO Intergovernmental Oceonographic Commission (IOC) and in particular its Intergovernmental Coordinating Group (ICG) to coordinate and give recommendations for such a development. Therefore the Decision Support System presented here is designed to be modular, extensible and interoperable (Raape et al., 2010).
Decision Support Tools for Cloud Migration in the Enterprise  [PDF]
Ali Khajeh-Hosseini,Ian Sommerville,Jurgen Bogaerts,Pradeep Teregowda
Computer Science , 2011,
Abstract: This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective; this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.
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