A connection between computer science and fuzzy theory: midpoints and running time of computing

Following the mathematical formalism introduced by M. Schellekens [Elec- tronic Notes in Theoret. Comput. Sci. 1 (1995), 211-232] in order to give a common foundation for Denotational Semantics and Complexity Analysis, we obtain an application of the theory of midpoints for asymmetric distances de ned between fuzzy sets to the complexity analysis of algorithms and pro- grams. In particular we show that the average running time for the algorithm known as Largetwo is exactly a midpoint between the best and the worst case running time of computingPeer Reviewe

Fuzzy Logic in Medicine and Bioinformatics

The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions) and in bioinformatics (comparison of genomes)

Managing healthcare performance in analytical framework

Purpose – The purpose of the paper is to develop an integrated framework for performance management of healthcare services. Design/methodology/approach – This study develops a performance management framework for healthcare services using a combined analytic hierarchy process (AHP) and logical framework (LOGFRAME). The framework is then applied to the intensive care units of three different hospitals in developing nations. Numerous focus group discussions were undertaken, involving experts from the specific area under investigation. Findings – The study reveals that a combination of outcome, structure and process-based critical success factors and a combined AHP and LOGFRAME-based performance management framework helps manage performance of healthcare services. Practical implications – The proposed framework could be practiced in hospital-based healthcare services. Originality/value – The conventional approaches to healthcare performance management are either outcome-based or process-based, which cannot reveal improvement measures appropriately in order to assure superior performance. Additionally, they lack planning, implementing and evaluating improvement projects that are identified from performance measurement. This study presents an integrated approach to performance measurement and implementing framework of improvement projects

Benchmarking of health technologies distribution models: an investigation of Lombardy’s local health authorities

Purpose – The purpose of this paper is to develop a benchmarking framework for assessing the performance of the distribution models adopted by the local branches of National Health Services (NHSs) for delivering health technologies to patients at a local level, and to derive prescriptions for enhancing design and optimal management of the distribution models. Design/methodology/approach – The authors focussed the study on the distribution of absorbent devices for incontinence, adopting the analytic hierarchy process as a tool for developing the benchmarking framework. The authors applied the framework to the context of the Italian NHS with respect to the Lombard Local Health Authorities, assessing their performance in terms of operational efficiency and service quality. Findings – The developed framework constitutes a novel contribution, and it allows for generating prescriptions. Through its application to the context studied the authors found that a “one-size-fits-all” distribution model cannot be proposed, as regards both efficiency and effectiveness, since process standardization does not provide benefits or savings in all contexts. Rather, a total landed cost approach in the evaluation of the distribution practices must be adopted. Practical implications – This paper offers to managers and decision makers an innovative approach to the design of distribution models for health technologies. It provides policy makers with prescriptions to develop regulations fostering a comprehensive view of the factors for an optimal health technologies distribution at a local level. Originality/value – Given the dearth of scientific publications focussed on the distribution at the local level of health technologies, this paper significantly contributes to the existing body of knowledge and it offers an innovative framework which can be proficiently replicated in manifold contexts

An Extended Fuzzy Discrete Event System For Hiv/aids Treatment Regimen Selection

HIV/AIDS is a global problem. Its treatment is dependent on the physician experts\u27 opinion. A system which is capable of supporting the treatment decision will be desired. Recently, the HIV/AIDS treatment regimen selection system appeared in literature that utilized theory of fuzzy discrete event system (FDES) to capture the meaning of experts\u27 knowledge; a form of consensus involving estimated points and type-1 fuzzy sets. The goal was to assign exact matching regimens as close as possible to those regimens preferred by the experts for patients. The system performance was 80% of satisfaction level with the 35 retrospective patients. Extracting experts\u27 knowledge into the consensus forms would not be possible without being compromised by the experts. With equal respective experts, if one insists on his/her values, then the consensus would not be achieved. Conversely, the FDES theory would be no longer to handle such conflict. The theory of extended fuzzy discrete event system (EFDES) extended the FDES theory that type-2 fuzzy sets would be allowed to be used in the system. This dissertation is to apply the EFDES theory to the HIV/AIDS treatment regimen selection system. Seven scenarios of the diversity of experts\u27 knowledge representation were categorized for the system. The MATLAB was implemented to model the system. Genetic algorithm in MATLAB\u27s Direct Search Toolbox was used to search an optimal vector of 26 weights for system parameters regarding the experts\u27 regimen-choices. As the same input of the retrospective patient data for the FDES-based system, the overall means of simulation results of EFDES-based system demonstrated the degree of matching regimens being 80%. That result would be the same performance level of the FDES-based system as well. The EFDES-based system performance with self-learning provided the overall satisfaction level of above 80%. Moreover, the EFDES-based system with use of the type-2 fuzzy set gained the benefit on the extraction of diverse and uncertainty experts\u27 knowledge and expertise