IMASC - An Intelligent MultiAgent System for Clinical Decision Support

Czibula, Gabriela; Czibula, Istvan Gergely; Cojocar, Grigoreta Sofia; Guran, Adriana-Mihaela

doi:10.1109/cans.2008.28

Cited by 8 publications

(5 citation statements)

References 4 publications

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“…But no checking mechanism is there to check whether proposed diagnosis is correct or not, as well as here no group discussion mechanism is formalized to take a diagnosis decision correctly. Similarly in [6] authors have proposed an intelligent multi agent system, named IMASC for assisting physicians in their decision making tasks. Here also no group discussion mechanism is proposed to achieve correctness in decision.…”

Section: Related Workmentioning

confidence: 99%

Coordination ontology for multi agent based distributed decision making

Acharya

Dutta

2012

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing

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Software agents can take decisions to perform different tasks to achieve a goal independently. When a number of agents take decisions collaboratively in distributed environment to achieve same goal, they need to coordinate with each other in order to avoid inconsistencies. Coordination is the process of managing interactions between these agents by identifying and possibly resolving the inconsistencies which can occur between their activities. In this work we propose a methodology by which number of agents can take their decisions independently and collaboratively by maintaining coordination between them. We propose a concept of coordination ontology for distributed decision support system. It consists of set of rules in order to coordinate actions of different agents and make a decision to achieve a goal successfully.

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Section: Related Workmentioning

confidence: 99%

Coordination ontology for multi agent based distributed decision making

Acharya

Dutta

2012

2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing

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“…Agents are "sophisticated computer programs that act autonomously on behalf of their users, across open distributed environments to solve a growing number of complex problems" (Aref, 2003;Czibula et al, 2008;Quteishat et al, 2009;Ramchurn et al, 2004;Suriyakala and Sankaranarayanan, 2007). Nature has shown that complex collective behaviors become possible by very simple interactions among large number of agents (Camazine, 2003;Yeom, 2013).…”

Section: Advisor Agents and Reliabilitymentioning

confidence: 99%

Selecting the reliable supplier by using the advisor agents

Majd

Balakrishnan

Godazgar

2017

JBIM

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Purpose This paper aims to enhance the successful interaction between buyers and suppliers who use intelligent agents by presenting a computational model to detect the most reliable supplier agent according to advice of an advisor agent. Design/methodology/approach In this case, the authors study the most representative models in agent environments. According to these analysis criteria, a computational model was presented to compute the reliability of supplier agents and then select the most reliable one. To evaluate the proposed method, the experimentation was carried out in two stages. First, the average accuracy of model in computing the reliability was evaluated by comparing a random selection method. Second, the performance of the model in detecting the most reliable supplier was evaluated in an agent environment by applying trust network game as a simulator. Findings The experimental results revealed that the proposed method can detect the most reliable supplier accurately in both consistent and oscillating agent environments. Originality/value The authors believe that the proposed model will be beneficial to enhance the fulfillment of purchasing between buyers and suppliers.

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“…Regarding the design and development of CDSS, the use of agent technology is not new, and several works have been proposed in the literature ( [2][3][4][5][6]).…”

Section: Related Workmentioning

confidence: 99%

“…In spite of the growing multiplicity of CDSS and their effectiveness certified in the decision making tasks at the time and the location of care, the state of the art of the existing CDSS ( [2][3][4][5][6]) emphasizes four main challenges that require to be resolved. The first challenge is that the clinical data that must be entered is already contained elsewhere in a digital form in that hospital's system, and some CDSSs (alert system, drug-drug detection system, medicinal errors prevention system, etc.)…”

Section: Introductionmentioning

confidence: 99%

Coupling clinical decision support system with computerized prescriber order entry and their dynamic plugging in the medical workflow system

Bouzguenda

Turki

2012

2012 International Conference on Information Technology and E-Services

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Abstract. This work deals with coupling Clinical Decision Support System (CDSS) with Computerized PrescriberOrder Entry (CPOE) and their dynamic plugging in the medical Workflow Management System (WfMS). First, in this paper we argue some existing CDSS representative of the state of the art in order to emphasize their inability to deal with coupling with CPOE and medical WfMS. The multi-agent technology is at the basis of our proposition since (i) it provides natural abstractions to deal with distribution, heterogeneity and autonomy which are inherent to the previous systems (CDSS, CPOE and medical WfMS), and (ii) it introduces powerful concepts such as organizations, goals and roles useful to describe in details the coordination of the different components involved in these systems. In this paper, we also propose a Multi-Agent System (MAS) to support the coupling CDSS with CPOE. Finally, we show how we integrate the proposed MAS in the medical workflow management system which is also based on collaborating agents.

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IMASC - An Intelligent MultiAgent System for Clinical Decision Support

Cited by 8 publications

References 4 publications

Coordination ontology for multi agent based distributed decision making

Coordination ontology for multi agent based distributed decision making

Selecting the reliable supplier by using the advisor agents

Coupling clinical decision support system with computerized prescriber order entry and their dynamic plugging in the medical workflow system

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