Search results for "Decision support system"

An ontological-based knowledge organization for bioinformatics workflow management system

2012

Motivation and Objectives In the field of Computer Science, ontologies represent formal structures to define and organize knowledge of a specific application domain (Chandrasekaran et al., 1999). An ontology is composed of entities, called classes, and relationships among them. Classes are characterized by features, called attributes, and they can be arranged into a hierarchical organization. Ontologies are a fundamental instrument in Artificial Intelligence for the development of Knowledge-Based Systems (KBS). With its formal and well defined structure, in fact, an ontology provides a machine-understandable language that allows automatic reasoning for problems resolution. Typical KBS are E…

Retail pricing decisions and product category competitive structure

2010

This study addresses the use of demand forecasting techniques by retailers to support their decision making. Specifically, the authors propose a pricing decision support model for retailers to estimate optimal prices, whose output depends on the configuration of a supporting measurement model. The measurement model is a demand function that relates sales and prices within the category; optimal prices are those whose effects on demand and retail margins maximize the category's profitability. This investigation focuses particularly on the role of competitive structure, such that the authors consider two types of price competition asymmetries for demand forecasting: those depending on the bran…

Prediction of lncRNA-Disease Associations from Tripartite Graphs

2021

The discovery of novel lncRNA-disease associations may provide valuable input to the understanding of disease mechanisms at lncRNA level, as well as to the detection of biomarkers for disease diagnosis, treatment, prognosis and prevention. Unfortunately, due to costs and time complexity, the number of possible disease-related lncRNAs verified by traditional biological experiments is very limited. Computational approaches for the prediction of potential disease-lncRNA associations can effectively decrease time and cost of biological experiments. We propose an approach for the prediction of lncRNA-disease associations based on neighborhood analysis performed on a tripartite graph, built upon …

Corrigendum to “Off-line control of the postprandial glycemia in type 1 diabetes patients by a fuzzy logic decision support” [Expert Systems with App…

2012

Demonstration of Semantic Web-based Medical Ontologies and Clinical Decision Support Systems

2016

Master's thesis in Information- and communication technology IKT590 - University of Agder 2016 Konfidensiell til / confidential until 01.01.2022

Ontology-based clinical decision support system applied on diabetes

2017

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Medical diagnosis is a multi-step process which is complex as it requires the consideration of many factors. Additionally, the accuracy of diagnosis varies depending on the skill and knowledge a physician has in the medical field. Using ICT solution, the physicians can be assisted so that they can make an accurate decision. Many applications have been developed to enhance physician performance and improve the patient outcome, however, the quality of these applications varies depending on knowledge representation methodology and reasoning approach adopted. Nowadays, ontology is being used in many clin…

Designing Ethical AI in the Shadow of Hume’s Guillotine

2020

Artificially intelligent systems can collect knowledge regarding epistemic information, but can they be used to derive new values? Epistemic information concerns facts, including how things are in the world, and ethical values concern how actions should be taken. The operation of artificial intelligence (AI) is based on facts, but it require values. A critical question here regards Hume’s Guillotine, which claims that one cannot derive values from facts. Hume’s Guillotine appears to divide AI systems into two ethical categories: weak and strong. Ethically weak AI systems can be applied only within given value rules, but ethically strong AI systems may be able to generate new values from fac…

Road Functional Classification Using Pattern Recognition Techniques

2019

The existing international standards suggest a methodology to assign a specific functional class to a road, by the values of some features, both geometrical and use-related. Sometimes, these characteristics are in contrast with each other and direct the analyst towards conflicting classes for a road or, worse, one or more of these features vary heterogeneously along the road. In these conditions, the analyst assigns the class that, by his capability and experience, he retains the most appropriate, in a very subjective way. On the contrary, the definition of an automatic procedure assuring an objective identification of the most appropriate functional class for each road would be desirable. …

Sustainability focused decision-making in building renovation

2017

Abstract An overview of recent research related to building renovation has revealed that efforts to date do not address sustainability issues comprehensively. The question then arises in regard to the holistic sustainability objectives within building renovation context. In order to deal with this question, the research adopts a multi-dimensional approach involving literature review, exploration of existing assessment methods and methodologies, individual and focus group interviews, and application of Soft Systems Methodologies (SSM) with Value Focused Thinking (VFT). In doing so, appropriate data about sustainability objectives have been collected and structured, and subsequently verified …

Visualizations for Decision Support in Scenario-based Multiobjective Optimization

2021

Reproducibility artifacts for: Babooshka Shavazipour, Manuel López-Ibáñez, and Kaisa Miettinen. Visualizations for Decision Support in Scenario-based Multiobjective Optimization. Information Sciences, 2021. doi:10.1016/j.ins.2021.07.025. Abstract: We address challenges of decision problems when managers need to optimize several conflicting objectives simultaneously under uncertainty. We propose visualization tools to support the solution of such scenario-based multiobjective optimization problems. Suitable graphical visualizations are necessary to support managers in understanding, evaluating, and comparing the performances of management decisions according to all objec…