13,956 research outputs found

    Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

    Full text link
    Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. Computer technology can be employed to provide clinical decision support and treatment recommendations. The problem of natural language applications is that they lack formality and the interpretation is not consistent. Conversely, ontologies can capture the intended meaning and specify modeling primitives. Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS). The proposed DSS uses Case-Based Reasoning (CBR) to consider disease manifestations and provides physicians with treatment solutions from similar previous cases for reference. The proposed DSS supports natural language processing (NLP) queries. The DSS obtained 84.63% accuracy in disease classification with the help of the ontology

    Engineering Agent Systems for Decision Support

    Get PDF
    This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain

    Recruitment and selection processes through an effective GDSS

    Get PDF
    [[abstract]]This study proposes a group decision support system (GDSS), with multiple criteria to assist in recruitment and selection (R&S) processes of human resources. A two-phase decision-making procedure is first suggested; various techniques involving multiple criteria and group participation are then defined corresponding to each step in the procedure. A wide scope of personnel characteristics is evaluated, and the concept of consensus is enhanced. The procedure recommended herein is expected to be more effective than traditional approaches. In addition, the procedure is implemented on a network-based PC system with web interfaces to support the R&S activities. In the final stage, key personnel at a human resources department of a chemical company in southern Taiwan authenticated the feasibility of the illustrated example.[[notice]]補正完畢[[journaltype]]國內[[incitationindex]]SCI[[incitationindex]]E

    Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

    Get PDF
    While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

    A Conceptual Framework for Definition of the Correlation Between Company Size Categories and the Proliferation of Business Information Systems in Hungary Download article

    Get PDF
    Based on a conceptual model, this paper aims to explore the background of the decision-making process leading to the introduction of business information systems among enterprises in Hungary. Together with presenting the problems arising in the course of the implementation of such systems, their usage patterns are also investigated. A strong correlation is established between the size of an enterprise, the scope of its business activities and the range of the business information systems it applies

    EU WATER POLICY: RESEARCH DEVELOPMENTS AND NEW MANAGEMENT TOOLS

    Get PDF
    At the end of 2000, the European Commission published its Water Framework Directive (WFD) in the Official Journal of the European Communities (2000/60/EC). This new legislation provides for achieving the sustainable management of water resources through its 26 articles that focus primarily on the improvement and protection of the quality of European water resources. The WFD adopts an integrated approach, based upon general principles deriving mainly from four disciplinary approaches, Geography; Ecology; Economics and Sociology. The new challenges posed to the people responsible for the management of water resources across the European Union include the "marrying" of existing national policies with the stipulations of the WFD. Research can support this transition by identifying compatibility and conflicts between legislative instruments, and by encouraging trans-national cooperative relationships. A relevant role of research is also foreseen in providing criteria and tools for conflict resolution by representing the goals of sustainable management in an objective and transparent way. The elaboration required for making planning decisions are increasing in number and complexity, requiring tools that help to organise and communicate the data that should be used to describe the decision context in terms of sustainability, in a holistic way by including environmental, economic and social information. These problems are being addressed by the MULINO Project, a 3-year research program aiming at producing a Decision Support System that will assist water managers in responding to the evolution of policies and management methodologies. The development of the system, which will be prepared in a software format, is being steered by a group of people from European water authorities. This steering committee is contributing to the policy analysis component of the research and to the software design which aims to be applicable in five different national contexts. This paper addresses the challenges and innovations that have been encountered in the second phase of research in which the first prototype of the software has been developed to operate in specific decision situations in each of MULINO's six case studies.Sustainable water management, EU policy, DSS tool, Resource /Energy Economics and Policy,

    How and Why Decision Models Influence Marketing Resource Allocations

    Get PDF
    We study how and why model-based Decision Support Systems (DSSs) influence managerial decision making, in the context of marketing budgeting and resource allocation. We consider several questions: (1) What does it mean for a DSS to be "good?"; (2) What is the relationship between an anchor or reference condition, DSS-supported recommendation and decision quality? (3) How does a DSS influence the decision process, and how does the process influence outcomes? (4) Is the effect of the DSS on the decision process and outcome robust, or context specific? We test hypotheses about the effects of DSSs in a controlled experiment with two award winning DSSs and find that, (1) DSSs improve users' objective decision outcomes (an index of likely realized revenue or profit); (2) DSS users often do not report enhanced subjective perceptions of outcomes; (3) DSSs, that provide feedback in the form of specific recommendations and their associated projected benefits had a stronger effect both on the decision making process and on the outcomes.Our results suggest that although managers actually achieve improved outcomes from DSS use, they may not perceive that the DSS has improved the outcomes. Therefore, there may be limited interest in managerial uses of DSSs, unless they are designed to: (1) encourage discussion (e.g., by providing explanations and support for the recommendations), (2) provide feedback to users on likely marketplace results, and (3) help reduce the perceived complexity of the problem so that managers will consider more alternatives and invest more cognitive effort in searching for improved outcomes.marketing models;resource allocation;DSS;decision process;decision quality

    Integration of decision support systems to improve decision support performance

    Get PDF
    Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

    Get PDF
    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types
    corecore