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Using Community Detection Techniques to Discover Non-Explicit Relationships in Neurorehabilitation Treatments

机译:利用社区检测技术发现神经痛治疗中的非明确关系

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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.
机译:患者和专业人员在复杂的临床结构域之间的相互作用,如神经晕厥,始终是一个复杂的过程,其中需要在短时间内的关键决策,并且每个决定对患者产生严重影响。在这种情况下,决定哪些是最合适的干预措施并不是一项容易的任务,因为这些患者同时呈现了几种损伤,多次诊断和所需的复杂跨学科方法。在这种情况下,已经开发了一种基于ICF的方法和工具,以探索患者损伤和治疗目标之间的关系。基于图形分析的提出方法用于分析一套遭受脑损伤的1960名患者。实现结果表明,所提出的方法能够找到非明确的关系。本研究构成了设计临床决策支持工具的第一步,用于神经晕船。

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