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

Ltifi, Hela; Benmohamed, Emna; Kolski, Christophe; Ayed, Mounir Ben

doi:10.1142/s0219622019500470

Cited by 22 publications

(7 citation statements)

References 47 publications

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“…For this reason, evaluating the utility and usability of a DSS based on the proposed autonomous decision-making process represents a difficult task. Nevertheless, its efficiency for attributing the adequate decision can be further ameliorated inspired by [ 63 – 66 ], and [ 67 ] by integrating the physician in the decision-making process via the visualization.…”

Section: Discussionmentioning

confidence: 99%

Integrated Bayesian and association-rules methods for autonomously orienting COVID-19 patients

Thaljaoui

Khediri

Benmohamed

et al. 2022

Med Biol Eng Comput

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The coronavirus infection continues to spread rapidly worldwide, having a devastating impact on the health of the global population. To fight against COVID-19, we propose a novel autonomous decision-making process which combines two modules in order to support the decision-maker: (1) Bayesian Networks method–based data-analysis module, which is used to specify the severity of coronavirus symptoms and classify cases as mild, moderate, and severe, and (2) autonomous decision-making module–based association rules mining method. This method allows the autonomous generation of the adequate decision based on the FP-growth algorithm and the distance between objects. To build the Bayesian Network model, we propose a novel data–based method that enables to effectively learn the network’s structure, namely, MIGT-SL algorithm. The experimentations are performed over pre-processed discrete dataset. The proposed algorithm allows to correctly generate 74%, 87.5%, and 100% of the original structure of ALARM, ASIA, and CANCER networks. The proposed Bayesian model performs well in terms of accuracy with 96.15% and 94.77%, respectively, for binary and multi-class classification. The developed decision-making model is evaluated according to its utility in solving the decisional problem, and its accuracy of proposing the adequate decision is about 97.80%. Graphical abstract

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Section: Discussionmentioning

confidence: 99%

Integrated Bayesian and association-rules methods for autonomously orienting COVID-19 patients

Thaljaoui

Khediri

Benmohamed

et al. 2022

Med Biol Eng Comput

Self Cite

View full text Add to dashboard Cite

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“…Concerning the third research line in this topic, almost all the papers in our pool mentioned supporting decision-makers in some way, though some of them dedicated their work to providing support for decision-making. Ltifi et al (2020) and Alves et al (2020) managed to combine data mining techniques with data visualizations to enhance decisionmaking. Ltifi et al (2020) claimed that valuable patterns can be extracted from data by employing Decision Support Systems (DSS) based on data mining.…”

Section: State Of the Art In Each Categorymentioning

confidence: 99%

“…Ltifi et al (2020) and Alves et al (2020) managed to combine data mining techniques with data visualizations to enhance decisionmaking. Ltifi et al (2020) claimed that valuable patterns can be extracted from data by employing Decision Support Systems (DSS) based on data mining. To transit from these patterns to knowledge, they proposed a generic approach to help decision-makers take advantage of this knowledge, by using a common visual analytics process.…”

Section: State Of the Art In Each Categorymentioning

confidence: 99%

Internet of Things Data Visualization for Business Intelligence

Khorasani

Chalmeta

2024

Big Data

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This study contributes to the research on Internet of Things data visualization for business intelligence processes, an area of growing interest to scholars, by conducting a systematic review of the literature. A total of 237 articles published over the past 11 years were obtained and compared. This made it possible to identify the top contributing and most influential authors, countries, publishers, institutions, papers and research findings, together with the challenges facing current research. Based on these results, this work provides a thorough insight into the field by proposing four research categories (Technology infrastructure, Case examples, Final-user experience, and Big Data tools), together with the development of these research streams over time and their future research directions.

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“…e method introduces the singular value decomposition (SVD) algorithm as well as the translation, rotation, and scaling matrices required for colour mapping using the content image and the reference image covariance, and then the result image is obtained after several matrix operations [7]. e histogram matching technique is used for colour transfer.…”

Section: Related Workmentioning

confidence: 99%

Research and Implementation of Colour Optimal Matching Model for Art Design Based on Bayesian Decision-Making

Zhai¹

2022

Mathematical Problems in Engineering

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This paper presents an in-depth study and analysis of the colour optimal matching model in art design through the method of Bayesian decision-making and the colour optimal matching model designed and applied to practice. Although Bayesian conditional theory constructs a representation theorem for causal decision theory, eliminating the formal differences between evidence decision theory and causal decision theory and reflecting their common intrinsic form. However, it still does not resolve the conflict between causal and evidential decision theories, but only translates it into a different interpretation of state parsing, and the choice of interpretation still comes from people’s different intuitive understanding of rationality. To address the problem that the colour information of the target image in the traditional recolouring method easily interferes with the recolouring process and affects the colour effect of the resulting image, a new method of recolouring based on the centralization constraint is proposed in the paper. A new method of colour transfer based on random walk image segmentation is proposed. First, an improved random walk image segmentation method is introduced to segment the reference image and the content image to obtain a more reasonable segmentation region, which can enhance the hierarchy of the resulting image. Second, the proposed colour transfer strategy performs feature matching in the corresponding region to achieve colour transfer. Finally, the structure-preserving filter is introduced to further optimize the resulting image to effectively improve the visual effect of the resulting image. Extensive experimental results show that the proposed method can achieve significantly better-quality results than the colour clustering-based colour transfer method. The experimental analysis shows that the newly designed comprehensive objective evaluation index of colour transfer in the paper can effectively solve the problem of the one-sidedness of a single evaluation index and can achieve highly consistent evaluation results with subjective evaluation.

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

Cited by 22 publications

References 47 publications

Integrated Bayesian and association-rules methods for autonomously orienting COVID-19 patients

Integrated Bayesian and association-rules methods for autonomously orienting COVID-19 patients

Internet of Things Data Visualization for Business Intelligence

Research and Implementation of Colour Optimal Matching Model for Art Design Based on Bayesian Decision-Making

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