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Adapted Visual Analytics Process for Intelligent Decision-Making: Application in a Medical Context
International Journal of Information Technology & Decision Making ( IF 4.9 ) Pub Date : 2019-12-10 , DOI: 10.1142/s0219622019500470
Hela Ltifi 1 , Emna Benmohamed 1 , Christophe Kolski 2 , Mounir Ben Ayed 1
Affiliation  

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.

中文翻译:

适应智能决策的可视化分析过程:在医学环境中的应用

在过去几年中,针对智能决策任务的可视化分析的理论和实践研究取得了显着进展。智能决策支持系统 (IDSS) 通过涉及可视化和数据挖掘技术,引入了从原始数据到决策的有效路径。基于数据挖掘的 DSS 从数据中产生潜在的有趣模式。从提取的模式到知识的过渡是一项微妙的任务。在这种情况下,我们建议采用一种通用的可视化分析流程来创建一条路径,使用户(决策者)能够通过与模式交互来自动探索和直观地提取洞察力。这个提议的灵感来自于将传统的可视化分析概念与知识可视化的心理模型相结合。这个想法是结合对模式的自动和可视化分析,以生成用于决策的知识。为了验证我们的提议,我们已将其应用于一个医学案例研究,以对抗重症监护室的医院感染。根据实用性和可用性维度对开发的平台进行了评估。
更新日期:2019-12-10
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