International Journal of Man-Machine Studies
Cognitive Fuzzy Modeling for Enhanced Risk Assessment in a Health Care Institution
IEEE Intelligent Systems
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Confidence Transformation for Combining Classifiers
Pattern Analysis & Applications
Brain tumor characterization using the soft computing technique of fuzzy cognitive maps
Applied Soft Computing
Fuzzy Cognitive Maps in modeling supervisory control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Fuzzy cognitive map architectures for medical decision support systems
Applied Soft Computing
Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps
Information Sciences: an International Journal
A new hybrid method using evolutionary algorithms to train Fuzzy Cognitive Maps
Applied Soft Computing
Genetic learning of fuzzy cognitive maps
Fuzzy Sets and Systems
Modelling grey uncertainty with Fuzzy Grey Cognitive Maps
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Applications
Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Applications
Fuzzy Modeling and Control
Proceedings of the Seventeenth Western Canadian Conference on Computing Education
RuleML representation and simulation of Fuzzy Cognitive Maps
Expert Systems with Applications: An International Journal
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Two thirds of American adults are now obese or overweight, and this proportion continues to increase. Primary care doctors are placed at the front lines in addressing the obesity problem. However, they often experience difficulties in tackling the complex problem of obesity by reducing it to a simple matter of diet and exercise that ignores the underlying psychosocial mechanisms even though many can be modified. We propose the first fuzzy cognitive map for the diagnosis of obesity based on psychosocial features. In our model, the existence of relationships between factors relies on a thorough literature review, and the strength of these relationships was estimated by a team of experts. The experts' estimations were converted to values used by our model through different techniques. We found that the choice of technique made little difference to the model's prediction. Through test cases, we show that small descriptions of patients' cases can be used for diagnosis. These descriptions could be obtained by filling a questionnaire before consulting with a doctor, therefore limiting the increase in consultation time while providing a useful guidance for possible behaviour change.