Abstract：
Diabetes is a non-communicable disease that has reached epidemic proportions, affecting 537 million people globally. Artificial Intelligence can support patients or clinicians in diabetes nutrition therapy - the first medical therapy in most cases of Type 1 and Type 2 diabetes. In particular, ontology-based recommender and decision support systems can deliver a computable representation of experts\' knowledge, thus delivering patient-tailored nutritional recommendations or supporting clinical personnel in identifying the most suitable diet. This work proposes a systematic literature review of the domain ontologies describing diabetes in such systems, identifying their underlying conceptualizations, the users targeted by the systems, the type(s) of diabetes tackled, and the nutritional recommendations provided. This review also delves into the structure of the domain ontologies, highlighting several aspects that may hinder (or foster) their adoption in recommender and decision support systems for diabetes nutrition therapy. The results of this review process allow to underline how recommendations are formulated and the role of clinical experts in developing domain ontologies, outlining the research trends characterizing this research area. The results also allow for identifying research directions that can foster a preeminent role for clinical experts and clinical guidelines in a cooperative effort to make ontologies more interoperable - thus enabling them to play a significant role in the decision-making processes about diabetes nutrition therapy.
摘要：
糖尿病是一种非传染性疾病，已达到流行病的程度，影响全球5.37亿人。人工智能可以支持患者或临床医生进行糖尿病营养治疗-这是大多数1型和2型糖尿病病例的第一种药物治疗。特别是,基于本体的推荐器和决策支持系统可以提供专家知识的可计算表示，从而提供患者定制的营养建议或支持临床人员确定最合适的饮食。这项工作提出了对描述此类系统中糖尿病的领域本体的系统文献综述，确定它们的潜在概念化，系统针对的用户，解决了糖尿病的类型，以及提供的营养建议。这篇综述还深入研究了领域本体的结构，强调可能阻碍（或促进）糖尿病营养治疗的推荐和决策支持系统采用它们的几个方面。此审查过程的结果可以强调如何制定建议以及临床专家在开发领域本体论中的作用，概述了这一研究领域的研究趋势。研究结果还可以确定研究方向，这些研究方向可以促进临床专家和临床指南在合作努力中发挥突出作用，使本体更具互操作性-从而使它们能够在糖尿病营养治疗的决策过程中发挥重要作用。
