Fuzzy cognitive map architectures for medical decision support systems

Stylios, Chrysostomos; Georgopoulos, Voula C.; Malandraki, Georgia A.; Chouliara, Spyridoula

doi:10.1016/j.asoc.2007.02.022

Cited by 170 publications

(56 citation statements)

References 14 publications

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“…Kosko (1986) applied fuzzy causal function (i.e., weighting the edges, from −1 to 1) to the relationships, creating 'Fuzzy Cognitive Maps' (FCM). Recent scientific studies have used cognitive mapping techniques in various domains, such as management studies (Pinch et al, 2010), finance (Koulouriotis et al, 2005) and medical sciences (Stylios et al, 2008;Papageorgiou, 2011). In an organizational setting, the Strategic Options Development and Analysis (SODA) technique has been developed by Colin Eden and Fran Ackermann (Ackermann and Eden, 2010).…”

Section: Introductionmentioning

confidence: 99%

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Vanwindekens

Stilmant

Baret

2013

Ecological Modelling

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Section: Introductionmentioning

confidence: 99%

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Vanwindekens

Stilmant

Baret

2013

Ecological Modelling

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“…Therefore, integration of a case based reasoning (CBR) module into the existing FCM can be a solution to the stated problem. The CBR-augmented FCM decision support system of 15) is particularly suitable as it is capable of making decisions for a new case with respect to the most similar one.…”

Section: Statistical Case Based Reasoning (Cbr)mentioning

confidence: 99%

A New Path Estimation Strategy for Predicting Blind Persons′ Motion in Indoor Environments

Motlagh

Hong

Ramli

et al. 2009

Journal of Asian Architecture and Building Engineering

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Research on the characteristics of spatial cognition without vision is used to improve the design of indoor environments to be safer for blind and visually handicapped persons. A fuzzy cognitive map (FCM) decision mechanism is presented for modeling path planning strategies adopted by blind travelers including wallfollowing, and shortcutting through the environment. A statistical case based reasoning (CBR) strategy is introduced for anticipating the points of switch between the two mentioned behaviours along the path. The combination of CBR and FCM modules provided a robust model of decision making which can be used for predicting blind motions. In this research, 51 eye-masked subjects contributed for obtaining the path patterns and for validating the results obtained using the proposed path prediction approach.

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“…There are proposals using FCMs for many applications and in different scientific fields. FCMs have been applied to analyse extended graph theoretic behaviour, to make decision analysis [14] and cooperate distributed agents [15], they are used as structures for automating human problem solving skills and as behavioural models of virtual worlds [16], and in many other fields. As decision makers activate a temporary mental representation in their memory based on their previous experiences or existing knowledge or preferences, we centred in how to apply FCMs to analyse traveling decision making processes of individuals.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

León¹,

Nápoles²,

Bello³

et al. 2013

IJCIS

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Although the individuals" transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations from individuals and convert them into computational structures is defined. For the creation of knowledge bases the use of Knowledge Engineering is accounted and later on the data is transferred into structures based on Fuzzy Cognitive Maps. Once the maps are created, their performances get improved through the use of a Particle Swarm Optimisation algorithm as a learning method, readjusting its predicting capacity from stored scenarios, where individuals left their preferences in front of random situations. Another important result is clustering the maps for knowledge discovery. This permits to find useful groups of individuals that policymakers can use for simulating new rules and policies. After related maps are identified, to merge them as a unique structure could benefit for different usages. Therefore an aggregating procedure is elaborated for this task, constituting an alternative approach for selecting a centroid of a specific estimated group, and therefore having, in only one structure, the knowledge and behavioural acting from a collection of individuals. Learning, clustering and aggregation of Fuzzy Cognitive Maps are combined in a cascade experiment, with the intention of describing travellers" behaviour and change trends in different abstraction levels. The results of this approach will help transportation policy decision makers to understand the people"s needs in a better way, consequently will help them actualising different policy formulations and implementations.

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Fuzzy cognitive map architectures for medical decision support systems

Cited by 170 publications

References 14 publications

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems

A New Path Estimation Strategy for Predicting Blind Persons′ Motion in Indoor Environments

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

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