Temporal reasoning techniques for the analysis of interactions in the treatment of comorbid patients

Luca Anselma, Luca Piovesan, P. Terenziani
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Abstract

Clinical practice guidelines are assuming a major role in the medical area, to provide physicians with evidence-based recommendations for the treatment of single pathologies. The treatment of comorbid patients (i.e., patients affected by multiple diseases) is one of the main challenges for the modern healthcare. It requires the development of new methodologies, supporting physicians in the treatment of interactions between guidelines. Several Artificial Intelligence approaches have started to face such a challenging problem. However, current approaches have a substantial limitation: they do not take into account the temporal dimension. This is a strong limitation. For instance, the effects of two actions taken from different guidelines may potentially conflict, but practical conflicts happen only if effects of such actions overlaps in time. In this paper, we propose an approach to support the temporal detection of interactions. Artificial intelligence temporal reasoning techniques, based on temporal constraint propagation, are widely exploited to such a purpose.
分析合并症患者治疗中相互作用的时间推理技术
临床实践指南在医学领域发挥着重要作用,为医生提供治疗单一病理的循证建议。合并症患者(即患有多种疾病的患者)的治疗是现代医疗保健面临的主要挑战之一。它需要开发新的方法,支持医生在治疗指南之间的相互作用。一些人工智能方法已经开始面临这样一个具有挑战性的问题。但是,目前的方法有很大的局限性:它们没有考虑到时间方面。这是一个很大的限制。例如,从不同的指导方针中采取的两个行动的效果可能会潜在地冲突,但是只有当这些行动的效果在时间上重叠时才会发生实际冲突。在本文中,我们提出了一种支持相互作用时间检测的方法。基于时间约束传播的人工智能时间推理技术被广泛应用于这一目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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