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These authors concluded that for a sizeable number of chronic pain patients, Multidimensional Pain Inventory classifications may not be stable and need to be reconsidered [ 11, 13].
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We integrate fuzzy concepts with real inventory data and design a decision support system assisting a sensible multi-criteria inventory classification.
We propose an inventory classification system based on the fuzzy analytic hierarchy process (AHP), a commonly used tool for multi-criteria decision making problems.
We report on a study conducted in a small electrical appliances company and validate the design of the proposed multi-criteria inventory classification system and its underlying fuzzy AHP model.
In this paper we deal with the problem of designing a classifier able to learn the classification of existing units in inventory and then use it to classify new units according to their attributes in a multi-criteria ABC inventory classification environment.
In the two samples of fibromyalgia up to one third of the patients changed Multidimensional Pain Inventory classification at retest (Table 5).
The Multidimensional Pain Inventory Classification System – classifying patients into predefined subgroups labelled as adaptive copers, dysfunctional, and interpersonally distressed – is substantially stable.
In their samples of patients with low back pain and fibromyalgia up to one third of the patients changed Multidimensional Pain Inventory classification at retest.
This cross validation study examined the reliability of the Multidimensional Pain Inventory (MPI) and the stability of the Multidimensional Pain Inventory Classification System of the empirically derived subgroup classification obtained by cluster analysis in chronic musculoskeletal pain.
The authors concluded that for a sizeable number of chronic pain patients, Multidimensional Pain Inventory subgroup classifications may not be stable and need to be reconsidered [ 11, 13].
We made an inventory and classification of these landforms.
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