An Intelligent Multi Agent Design in Healthcare Management System

Sharma, Dharmendra; Shadabi, Fariba

doi:10.1007/978-3-540-78582-8_68

Cited by 9 publications

(7 citation statements)

References 10 publications

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“…A group of agents can collectively and collaboratively form a Multi Agent System (MAS) to perform complex and lengthy tasks [3].…”

Section: B Why Multi Agent?mentioning

confidence: 99%

“…Follow by an overview of two hybrid intelligent techniques that might be utilized as a new generation of predictive analytics for big data particularly for knowledge discovery in big data and decision making processes in social systems. The approaches presented in this research have been tested successfully in similar situations [3][4][5].…”

Section: Introductionmentioning

confidence: 95%

“…Such a hybrid approach can be considered as an effective approach for the development of intelligent decision support systems in health domain [3].…”

Section: Introductionmentioning

confidence: 99%

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The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

Sharma

Shadabi

2014

2014 IEEE Fourth International Conference on Big Data and Cloud Computing

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Social and health informatics has the potential of improving the general wellbeing and health of individuals. Although the structure and nature of health facilities and services in some countries may pose a challenge for a short while, such obstacles according to many studies will be streamlined in the near future. The widespread utilization and implementation of healthcare information system in the day-to-day health care operations will lead to cost effective clinical trials and selfhealthcare management. On the other hand, recent rapid development of computer technology in this area has introduced a data explosion challenge. This paper provides brief background information on Social Informatics and e-Health Systems. Follow by an overview of two hybrid intelligent techniques that might be utilized as a new generation of predictive analytics for big data particularly for knowledge discovery in big data and decision making processes in social systems.

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“…A group of agents can collectively and collaboratively form a Multi Agent System (MAS) to perform complex and lengthy tasks [3].…”

Section: B Why Multi Agent?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

See 1 more Smart Citation

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

Sharma

Shadabi

2014

2014 IEEE Fourth International Conference on Big Data and Cloud Computing

Self Cite

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“…As the complexity of the problems modeled in this paradigm grows, it is required that multiple agents can work together [2]- [4]. As a result, multi-agent system (MAS) engineering has been developed as a means of coordinating agents [5].…”

Section: Introductionmentioning

confidence: 99%

A formal model of persuasion dialogs for interactions among argumentative software agents

Muñoz¹,

Botía²

2009

jopha

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Abstract-Multi-agent systems (MAS) offer an approach to solve complex problems where data and control are inherently distributed among several agents. Normally, agents have to cope with conflicts based on inconsistent knowledge which arise when they exchange information. A relative common alternative to solve these conflicts is Argumentation. This technique allows agents to develop a coordination process based on the exchange of justifications supporting a piece of knowledge, with the aim of proving its validness. However, most argumentation frameworks are theoretical approaches to this problem. We have developed an Argumentation System Based on Ontologies (ASBO). It follows an engineering-oriented approach to materialize a software architecture which allows working with argumentation in MAS. Moreover, ASBO has also a formal model in the background. This paper introduces such formal model, in order to identify and unambiguously define the core elements that argumentation systems should include.

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“…In our architecture presented on Chapter 4, the agent package contains static and mobile agents, each one endowed with specialized capabilities and goals for helping the healthcare professionals check the availability of resources, and obtain information and detect abnormalities on their patients [236].…”

Section: Agent Packagementioning

confidence: 99%

Methodological support to develop interoperable applications for pervasive healthcare

Moraes¹

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The healthcare model currently being used in most countries will soon be inadequate, due to the increasing care costs of a growing population of elderly people, the rapid increase of chronic diseases, the growing demand for new treatments and technologies, and the relative decrease in the number of healthcare professionals with respect to the population increase. This healthcare model, which is centered on highly specialized people, located in large hospitals, needs to change into a distributed model, in order to produce faster responses and to allow patients to manage their own health. This centralized healthcare model also implies that patients and healthcare professionals have to move to the same place (a hospital or clinic) for the healthcare services to be delivered, and it is often expensive and inefficient. A distributed healthcare model that pervades the daily lives of the citizens is more appropriate to provide less expensive and more effective and timely healthcare, and characterizes Pervasive Healthcare. In Pervasive Healthcare, novel information and communication technologies are applied to support the provision of health services anywhere, at anytime and to anyone.This thesis aims at demonstrating the feasibility of using healthcare standards, ubiquitous computing technologies, service-oriented architecture principles, and software agents, to develop interoperable applications for exchanging messages in Pervasive Healthcare environments. This thesis presents a Reusable Architecture and a Message Generator that employ these technologies for achieving its aim. Our Reusable Architecture and Message Generator also meet the requirements of interoperability between heterogeneous healthcare information systems that are usually found in Pervasive Healthcare environments.In this work, a case study was performed in a realistic distributed healthcare environment, where three usage scenarios were defined in the cardiology domain: delivery of laboratory analysis results, schedule of an appointment for pacemaker evaluation, and support of a medical staff II ABSTRACT meeting to prepare for a cardiac surgery. Using the Reusable Architecture and the Message Generator, three applications were built for these scenarios, and they were employed and evaluated by both healthcare professionals and patients. The experiments were conducted in a distributed environment that consists of three cardiology clinics, one analysis laboratory, and the cardiology department of the Santa Casa Hospital of Marília (São Paulo, Brazil). The evaluation of these applications was carried out using the Technology Acceptance Model (TAM), since this model is generally considered as appropriate to explain technology acceptance. The evaluation involved a limited but representative set of healthcare professionals and patients.We showed that the methodology proposed in this thesis truly facilitates the development of Pervasive Healthcare. The proposed methodology preserves the investment in the legacy healthcare information systems and allow...

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An Intelligent Multi Agent Design in Healthcare Management System

Cited by 9 publications

References 10 publications

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

A formal model of persuasion dialogs for interactions among argumentative software agents

Methodological support to develop interoperable applications for pervasive healthcare

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