The use of modified constellation graph method for computer-aided classification of congenital heart diseases

Sekiya, Tatsuhiko; Watanabe, Arata; Saito, Mitsutoshi

doi:10.1109/10.83594

Cited by 10 publications

(3 citation statements)

References 13 publications

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“…x i = ( x i 1 , … , x ij , … , x ip ) is the observation vector of i -th sample. The main steps to construct the traditional constellation graph are as follows: 18,19…”

Section: Methodsmentioning

confidence: 99%

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A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Yang¹,

Kim²,

Ji-Yon³

2021

Proceedings of the Institution of Mechanical Engineers, Part L:

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Traditional constellation graphical method maps a multidimensional data into a 2D graph. In this paper, the drawback of the traditional semi-circular constellation graph is considered and a quadrant circular constellation graph is proposed to overcome the drawback. Moreover, a new materials selection MADM (multi-attribute decision making) method is proposed based on the quadrant circular constellation graph. This method is applied to select the best magnesium alloy material for automotive wheels. The numerical and graphical results show that AZ91 is the optimal material among the alternative materials such as AZ91, AM60, AM50, AZ31, ZE41, EZ33, ZE63 and ZC63. The result is compared with the results from the previous MADM methods from the viewpoint of Spearman’s rank correlation and deviation. Additionally, a sensitivity analysis to attribute weights is performed to test the robustness of the proposed method. Experimental results demonstrate that the proposed method is superior to the previous MADM methods. The proposed method is not only quantitative but also intuitive method. It could be widely used to materials selection problems in engineering practice.

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“…x i = ( x i 1 , … , x ij , … , x ip ) is the observation vector of i -th sample. The main steps to construct the traditional constellation graph are as follows: 18,19…”

Section: Methodsmentioning

confidence: 99%

“…Sekiya et al. 19 proposed the modified constellation graph method for computer-aided classification of congenital heart diseases. Sugano 20 proposed the generalized constellation graph transformation model for prediction and showed some examples of application to air pollution data.…”

Section: Introductionmentioning

confidence: 99%

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Yang¹,

Kim²,

Ji-Yon³

2021

Proceedings of the Institution of Mechanical Engineers, Part L:

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show abstract

“…This section works with the three-factor model to further analyse the collective information in the intermediate rurality indices. Constellation graphs were introduced in Wakimoto and Taguri (1978) as a means of obtaining a two dimensional representation of multi-dimensional data (see Mitzuta, 1994, Sekiya et al., 1991, for examples of its application). In this paper, they are employed to position local authorities in a domain encompassing the limits of rurality, namely rural and urban.…”

Section: Revisiting Cloke (1977)mentioning

confidence: 99%

Measuring and understanding the differences between urban and rural areas

Beynon

Crawley

Munday

2016

Environ Plann B Plann Des

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Understanding the factors that make a location more rural or urban is an important task for planners and policymakers. Traditional individual characteristics of rurality sometimes hide the more complex social as well as physical dynamics of a locality. This paper builds on early work which applied factor analysis to construct a single index of rurality. An approach is developed with a combined metric encompassing multiple measures. These are capable individually of defining rurality but together they deliver greater insight on more complex patterns and help to redefine the simple notion of rurality. The paper then utilises a novel graphical method, the constellation graph, providing a diagnostic and visual framework to aid planners when assessing the spatial dimensions of a locality.

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Modeling Paradigms for Medical Diagnostic Decision Support: A Survey and Future Directions

2011

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Use of computer based decision tools to aid clinical decision making, has been a primary goal of research in biomedical informatics. Research in the last five decades has led to the development of Medical Decision Support (MDS) applications using a variety of modeling techniques, for a diverse range of medical decision problems. This paper surveys literature on modeling techniques for diagnostic decision support, with a focus on decision accuracy. Trends and shortcomings of research in this area are discussed and future directions are provided. The authors suggest that-(i) Improvement in the accuracy of MDS application may be possible by modeling of vague and temporal data, research on inference algorithms, integration of patient information from diverse sources and improvement in gene profiling algorithms; (ii) MDS research would be facilitated by public release of de-identified medical datasets, and development of opensource data-mining tool kits; (iii) Comparative evaluations of different modeling techniques are required to understand characteristics of the techniques, which can guide developers in choice of technique for a particular medical decision problem; and (iv) Evaluations of MDS applications in clinical setting are necessary to foster physicians' utilization of these decision aids.

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The use of modified constellation graph method for computer-aided classification of congenital heart diseases

Cited by 10 publications

References 13 publications

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

A quantitative and intuitive materials selection multi-attribute decision-making method based on quadrant circular constellation graph

Measuring and understanding the differences between urban and rural areas

Modeling Paradigms for Medical Diagnostic Decision Support: A Survey and Future Directions

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