Mounir Ben Ayed

A user-centered approach for the design and implementation of KDD-based DSS: A case study in the healthcare domain

In this article we propose an approach for a decision support system (DSS) based on Knowledge Discovery from Databases (KDD). In such system, user must be involved throughout the decision-making process. In consequence we propose the integration of a Human-Computer Interaction (HCI) model into the development of DSS process based on KDD. The approach we propose is based on two systems development methods-the Unified Process (UP) from Software Engineering and the U model from HCI. In this article, we describe our combined approach (UP/U) and the way we used it to develop a DSS in a medical field.

Survey of information visualization techniques for exploitation in KDD

The last years witnessed a continued growth of the amount of data. The data analysis and exploration has become more and more difficult. So, it seems important to find means to visually represent this flood of data. Information visualization can help any user to get and understand information efficiently and implicate him/her in the data mining process thanks to our perception possibilities. The visualization domain proposes a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization techniques. We present also each technique, its advantages and disadvantages.

A human-centred design approach for developing dynamic decision support system based on knowledge discovery in databases

This paper presents a human-centred design approach for developing Decision Support Systems (DSS) based on a Knowledge Discovery in Databases (KDD) process. The KDD process generates a set of software modules. Our approach is based on a critical study of design methods. It uses the Unified Process (UP), which proposes a general framework; however, the UP does not include enough Human-Computer Interaction (HCI) elements. We suggest enriching the UP activities from the HCI perspective, adding HCI elements. The proposed approach is applied to a KDD-based Dynamic Medical DSS. Cet article présente une approche de conception centrée utilisateur pour le développement d’un systéme interactif d’aide à la décision (SIAD) basé sur un processus d’extraction de connaissances à partir de données (ECD). Le processus d’ECD aide généralement à générer un ensemble de modules logiciels. Notre approche est basée sur une étude critique des méthodes de conception. Elle utilise le Processus Unifié (PU), qui offre un cadre méthodologique générique. Néanmoins, le PU n’intégre pas assez d’éléments d’Interaction Homme-Machine (IHM). Nous proposons d’enrichir les activités du PU sous l’angle des IHM. L’approche proposée est appliquée à un Système Interactif d’Aide à la Décision Dynamique (SIADD) basé sur l’ECD.

Using visualization techniques in knowledge discovery process for decision making

The presence of large quantities of temporal data requires interactive analysis for decision-making. Interactive decision support system (DSS) based on knowledge discovery in databases (KDD) process proves to be useful. Temporal data visualization techniques are used in the KDD stages to increase the user participation as well as its confidence in the result in order to improve the decision support quality. Our applicative context is the fight against nosocomial infections in the intensive care unit.

Dynamic Decision Support System Based on Bayesian Networks

The improvement of medical care quality is a significant interest for the future years. The fight against nosocomial infections (NI) in the intensive care units (ICU) is a good example. We will focus on a set of observations which reflect the dynamic aspect of the decision, result of the application of a Medical Decision Support System (MDSS). This system has to make dynamic decision on temporal data. We use dynamic Bayesian network (DBN) to model this dynamic process. It is a temporal reasoning within a real-time environment; we are interested in the Dynamic Decision Support Systems in healthcare domain (MDDSS).

Interactive visual knowledge discovery from data-based temporal decision support system

The article aims to present a generic interactive visual analytics solution that provides temporal decision support using knowledge discovery from data modules together with interactive visual representations. It bases its design decisions on classification of visual representation techniques according to the criteria of temporal data type, periodicity, and dimensionality. The design proposal is applied to an existing medical knowledge discovery from data–based decision support system aiming at assisting physicians in the fight against nosocomial infections in the intensive care units. Our solution is fully implemented and evaluated.

HCI-enriched approach for DSS development: the UP/U approach

In this paper we propose an approach aiming to integrate Human-Computer Interaction (HCI) aspects in decision support system (DSS) development. We propose an approach combining two methods: one issued from software engineering field (the Rational Unified Process) and the other one from the HCI field (the U model). We have tested our approach in a DSS set up in the healthcare domain: the supervision of nosocomial infections in an intensive care unit.

Combination of cognitive and HCI modeling for the design of KDD-based DSS used in dynamic situations

Recent work in dynamic decision support systems (DSS) has taken impressive steps toward data preparation and storage, intelligent data mining techniques, and interactive visualization. However, it remains difficult to deal with the uncertainty and complexity generated by the Knowledge Discovery in Databases (KDD). This paper launches the challenge by introducing cognitive modeling for specifying decision-maker behaviors more naturally and intuitively. It consists in introducing cognitive modeling for dynamic situations involving visual KDD-based dynamic DSS. This research work presents an adaptation of a well-known cognitive model under the KDD specificities. We provide cognitive modeling application in visual KDD-based dynamic DSS for the fight against nosocomial infections in an intensive care unit. Finally, we built a series of evaluations verifying the systems utility and usability. Display Omitted To ensure and improve the human-computer interaction in dynamic decision support systems based on knowledge discovery in data, our research context concerns the modeling of the decision-maker behavior to accomplish complex dynamic decision-making tasks and producing logically valid predictions.The methodological contribution consists in designing visual KDD-based Dynamic DSS using a cognitive model. We propose to adapt the well-known Hoc and Amalberti model cognitive model under the KDD specificities.The approach was applied in the medical domain for the fight against nosocomial infections in the ICU.The evaluation of this proposal under the utility and usability dimensions shows satisfactory results.

Swarm intelligence and multi agent system in healthcare

The domain of Healthcare is characterized by difficulty, dynamism and variety. In the 21st century healthcare represents different challenges (the increasing cost of care and the growing of populations). For that, Agent Technology can provide better healthcare than the traditional medical system. In the hospital, several types of medical problems can be solved by agents. As examples of problems, which emerge in the hospital, we mention: collaboration between hospital wards, elaborations of diagnostics, the collection of information about patients etc. The adaptation of cooperative Multi Agent System (MAS) can solve these problems. In this regard, this study proposes a general architecture that integrates Swarm Intelligence into Multi Agent healthcare System in order to make care as efficient as possible.

Mobile Cloud Computing in Healthcare System

Mobile Cloud Computing (MCC) is a potential technology for mobile web services. Accordingly, we assume that MCC is likely to be of great avail to healthcare domain. MCC offers new kinds of services and facilities for patients and caregivers. In this regard, we have tried to propose a new mobile medical web service system. The proposed system called Medical Cloud Multi Agent System is a complex system which integrates MCC and Multi Agent System in healthcare with view to improving healthcare system.