Adapted Visual Analytics Process for Intelligent Decision-Making: Application in a Medical Context

Hela Ltifi (), Emna Benmohamed (), Christophe Kolski () and Mounir Ben Ayed ()
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Hela Ltifi: Research Groups in Intelligent Machines, University of Sfax National School of Engineers (ENIS), BP 1173, Sfax, 3038, Tunisia
Emna Benmohamed: Research Groups in Intelligent Machines, University of Sfax National School of Engineers (ENIS), BP 1173, Sfax, 3038, Tunisia
Christophe Kolski: #x2020;LAMIH-UMR CNRS 8201, Université Polytechnique Hauts-de-France, Valenciennes, France
Mounir Ben Ayed: Research Groups in Intelligent Machines, University of Sfax National School of Engineers (ENIS), BP 1173, Sfax, 3038, Tunisia

International Journal of Information Technology & Decision Making (IJITDM), 2020, vol. 19, issue 01, 241-282

Abstract: The theoretical and practical researches on Visual Analytics for intelligent decision-making tasks have remarkably advanced in the past few years. Intelligent Decision Support Systems (IDSS) introduce effective and efficient paths from raw data to decision by involving visualization and data mining technologies. Data mining-based DSS produces potentially interesting patterns from data. The transition from extracted patterns to knowledge is a delicate task. In this context, we propose to adapt a common visual analytics process for creating a path that enables the user (decision-maker) to automatically explore and visually extract insights by interacting with the patterns. This proposal is inspired from integrating traditional visual analytics concepts with the mental model of knowledge visualization. The idea is to combine an automatic and visual analysis of patterns to generate knowledge for the purpose of decision-making. To validate our proposal, we have applied it to a medical case study for the fight against Nosocomial Infections in Intensive Care Units. The developed platform was evaluated according to the utility and usability dimensions.

Keywords: Decision support system; data mining; visual analytics; knowledge; pattern (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219622019500470

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