Authors:
Paulo Freitas
1
;
Carlos Henggeler Antunes
2
and
Jorge Dias
1
Affiliations:
1
Institute of Systems and Robotics and University of Coimbra, Portugal
;
2
INESC Coimbra and University of Coimbra, Portugal
Keyword(s):
Multi-criteria models, Outranking methods, ELECTRE TRI, Mental disabilities, Alzheimer disease.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Decision Analysis
;
Decision Support Systems
;
Forecasting
;
Information Systems
;
Methodologies and Technologies
;
Operational Research
;
OR in Health
;
Pattern Recognition
;
Software Engineering
Abstract:
A multi-criteria model tackled by an outranking method devoted to the sorting problem is presented to support decision making in assessing individual mental disabilities using information required in the Clinical Dementia Rating scale. This diagnosis process is a critical factor for adapting treatments to the current stage of the disease and improving health care and quality of life. The criteria required in the Clinical Dementia Rating scale have been considered as an input for developing our multi-criteria model, the output of which is the classification of each individual under evaluation in a pre-defined ordered class (category) as an indicator of the revealed level of mental disabilities. A method based on the exploitation of an outranking relation for the sorting problem is used to compare the individual information according to multiple evaluation criteria with reference profiles (specified standards) that define the boundaries of the classes. This methodological approach is s
ubstantially different from the ones based on the aggregation of the different criteria using weighted-sums to produce a “common value” measure. The method requires meaningful technical parameters, such as weights (herein perceived as true importance coefficients of the multiple evaluation aspects), distinct thresholds to ascertain the outranking classification, and a cutting level establishing the exigency of the classification. A realistic example using the decision support system Iris is presented to illustrate the results.
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