|Title||Using community detection techniques to disc over non-explicit relationships in neurorehabilitation treatments|
|Publication Type||Conference Paper|
|Year of Publication||2017|
|Authors||Sanchez-Pinsach D, Arcos JLluis, Laxe S, Bernabeu M, Tormos JMaria|
|Conference Name||20th International Conference of the Catalan Association for Artificial Intelligence|
The interaction between patients and professionals in complex clinical domains, as in the case of Neurorehabilitation, is always a complex process where crucial decision making in a short period of time is required, and where every decision has a serious impact on the patient. In this situation, deciding which are the most appropriate interventions is not an easy task because these patients simultaneously present several impairments, multiple diagnoses, and required complex interdisciplinary approaches. In this context, a methodology and a tool based on ICF have been developed to explore the relationships between patient impairments and therapeutic goals. The proposed approach, based on graph analysis, was used to analyze a set of 1960 patients that suffered an Acquired Brain Injury. Results achieved show that the proposed methodology is able to find non-explicit relationships. This study constitute a first step to the goal of designing a clinical decision support tool for neurorehabilitation.
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