A web-based high-performance multicriteria decision support system for medical diagnosis

Rahimi, Shahram; Gandy, Lisa; Mogharreban, Namdar

doi:10.1002/int.20238

Cited by 16 publications

(10 citation statements)

References 6 publications

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“…Neural networks (Wilson, 1995;Maier et al, 2000;Jürgen & Arnold, 2003;Kahn, 2003;Bartlett, 2006;Flitman, 2006;Iyer & Sharda, 2009), data mining techniques (Bhandari et al, 1997), linear regression and neural network models (Condon et al, 1999), data envelopment analysis (Sueyoshi et al, 1999;Cooper et al, 2009), statistical analysis (Hoare, 2000;Summers et al, 2007), dynamic programming (Fry et al, 2007 and expert and fuzzy expert systems (Dežman et al, 2001;Rogulj et al, 2006;Papić et al, 2009) were used in these studies. The major drawbacks of these approaches include difficulty of updating the knowledge with new or improved information, long response time, difficulty of use and finally, low-quality decision support in some cases (Rahimi et al, 2007). Unlike previous works, this study utilizes fuzzy sets and MADM methods to evaluate players' performance and to select skilful players by using qualitative and quantitative attributes.…”

Section: Introductionmentioning

confidence: 99%

Development of a fuzzy decision support framework for complex multi‐attribute decision problems: A case study for the selection of skilful basketball players

Ballı

Korukoğlu

2012

Expert Systems

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The selection of skilful players is a complicated process due to the problem criteria consisting of both qualitative and quantitative attributes as well as vague linguistic terms. This study seeks to develop a decision support framework for the selection of candidates eligible to become basketball players through the use of a fuzzy multi‐attribute decision making (MADM) algorithm. The proposed model is based on fuzzy analytic hierarchy process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The model was employed in the Youth and Sports Center of Mugla, Turkey, with the participation of seven junior basketball players aged between 7 and 14. In the present study, physical fitness measurement values and observation values of technical skills were utilized. FAHP was used to determine the weights of the criteria and the observation values of technical skills by decision makers. Physical fitness measurement values were converted to fuzzy values by using a fuzzy set approach. Subsequently, the overall ranking of the candidate players was determined by the TOPSIS method. Results were compared with human experts’ opinions. It is observed that the developed model is more reliable to be used in decision making. The model architecture and experimental results along with illustrative examples are further demonstrated in the study.

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Section: Introductionmentioning

confidence: 99%

Development of a fuzzy decision support framework for complex multi‐attribute decision problems: A case study for the selection of skilful basketball players

Ballı

Korukoğlu

2012

Expert Systems

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“…In troubleshooting, rule-based expert systems have been used, where systems typically suggest possible actions after an operator enters the observed symptoms [12,4]. In a diagnostic process for building explanations of patient's observed temporal evolution, fuzzy logic has been used to make the representation of quantitative and qualitative imprecise temporal information possible [7,9]. This paper proposes a method for generating a Web-page based troubleshooter, which diagnoses troubles about computer system administration.…”

Section: Introductionmentioning

confidence: 98%

Web-Based Troubleshooter Generation for System Administration

Shimomura

Ikeda

Takahashi

2009

2009 WRI World Congress on Computer Science and Information Engineering

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This paper proposes a method for generating a Web-page based troubleshooter, which diagnoses troubles about computer system administration. This troubleshooter digs out several possible causes (hypotheses) from the current status of a trouble, and then examines those hypotheses in turn. After the cause is identified, it will present a solution to fix the trouble. To illustrate the status of a trouble, possible causes, examination methods and presentation of a solution, Web pages (hereafter, info pages) are used, which are defined in HTML code. From the info pages that explain each status of troubleshooting, the method this paper presents generates troubleshooter client/server interface, a stack of status history and titled links to the next info pages. This paper also describes two ways to easily implement this method on both of a client side and a server side.

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“…For instance, in supply chain management and logistics, the TOPSIS approach was used for supplier selection (Chen et al, 2006;Boran et al, 2009;Celik, 2010;Chen, 2011;Dalalah et al, 2011;Deng and Chan, 2011;Fazlollahtabar et al, 2011), the location problem (Chu, 2002;Yong, 2006;Ertuğrul, 2010;Kuo, 2011;Awasthi et al, 2011;Li et al, 2011) and the selecting service problems (Bottani and Rizzi, 2006;Kahraman et al, 2007;Lin and Tsai, 2009;Chamodrakas et al, 2011;Cheng et al, 2011). It was also used in energy management (Yan et al, 2011;Kaya and Kahraman, 2011;Boran et al, 2012), chemical engineering (Rao and Baral, 2011;Sun et al, 2011;Ramezani et al, 2011), health problem (Rahimi et al, 2007;Wang et al, 2010;La Scalia et al, 2011) and even for the new ground-air missile weapon system selection problem (Li et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

The Characteristic Objects Method: A New Distance‐based Approach to Multicriteria Decision‐making Problems

Sałabun

2014

Multi Criteria Decision Anal

144

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Multicriteria decision-making (MCDM) methods are concerned with the ranking of alternatives based on expert judgements made using a number of criteria. In the MCDM field, the distance-based approach is one popular method for obtaining a final ranking. The technique for order preference by similarity to the ideal solution (TOPSIS) is a commonly used example of this kind of MCDM method. The TOPSIS ranks the alternatives with respect to their geometric distance from the positive and negative ideal solutions. Unfortunately, two reference points are often insufficient, especially for nonlinear problems. As a consequence of this situation, the final result ranking is prone to errors, including the rank reversals phenomenon.This study proposes a new distance-based MCDM method: the characteristic objects method. In this approach, the preferences of each alternative are obtained on the basis of the distance from the nearest characteristic objects and their values. For this purpose, we have determined the domain and Fuzzy number set for all the considered criteria. The characteristic objects are obtained as the combination of the crisp values of all the Fuzzy numbers. The preference values of all the characteristic object are determined on the basis of the tournament method and the principle of indifference. Finally, the Fuzzy model is constructed and is used to calculate preference values of the alternatives, making it a multicriteria model that is free of rank reversal. The numerical example is used to illustrate the efficiency of the proposed method with respect to results from the TOPSIS method. The characteristic objects method results are more realistic than the TOPSIS results.

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A web-based high-performance multicriteria decision support system for medical diagnosis

Cited by 16 publications

References 6 publications

Development of a fuzzy decision support framework for complex multi‐attribute decision problems: A case study for the selection of skilful basketball players

Development of a fuzzy decision support framework for complex multi‐attribute decision problems: A case study for the selection of skilful basketball players

Web-Based Troubleshooter Generation for System Administration

The Characteristic Objects Method: A New Distance‐based Approach to Multicriteria Decision‐making Problems

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