A Domain-Specific Modeling Language for Specification of Clinical Scores in Mobile Health

Allan Fábio de Aguiar Barbosa, Francisco Silva, L. Coutinho, Davi Viana, A. Teles
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引用次数: 5

Abstract

Clinical scores are a widely discussed topic in health as part of modern clinical practice. In general, these tools predict clinical outcomes, perform risk stratification, aid in clinical decision making, assess disease severity or assist diagnosis. However, the problem is that clinical scores data are traditionally obtained manually, which can lead to incorrect data and result. In addition, by collecting biological/health data in real time from humans, the current mobile health (mHealth) solutions that computationally solve that problem are limited because those systems are developed considering the specificities of a single clinical score. This work is part of the MDD4ClinicalScores project that addresses the productivity in developing mHealth solutions for clinical scores through the use of Model Driven Development concepts. This paper focus in describing DSML4ClinicalScore, a high-level domain-specific modeling language that uses the Ecore metamodel to describe a clinical score specification. To propose the DSML4ClinicalScore we analysed 89 clinical scores to define the artifacts of this proposed Metamodel. In the end, a practical case study using this DSML is provided to validate the DSML4ClinicalScore Metamodel, and to show how to use the proposal in a clinical situation scenario.
用于移动医疗临床评分规范的领域特定建模语言
作为现代临床实践的一部分,临床评分在健康领域是一个被广泛讨论的话题。一般来说,这些工具预测临床结果,进行风险分层,帮助临床决策,评估疾病严重程度或辅助诊断。然而,问题是临床评分数据传统上是手工获取的,这可能导致数据和结果不正确。此外,通过实时收集人类的生物/健康数据,目前的移动健康(mHealth)解决方案在计算上解决了这个问题,因为这些系统是考虑到单个临床评分的特殊性而开发的。这项工作是MDD4ClinicalScores项目的一部分,该项目通过使用模型驱动开发概念,解决了为临床评分开发移动医疗解决方案的生产力问题。本文重点描述DSML4ClinicalScore,这是一种高级领域特定的建模语言,它使用Ecore元模型来描述临床评分规范。为了提出DSML4ClinicalScore,我们分析了89个临床分数来定义这个提议的元模型的伪像。最后,提供了一个使用该DSML的实际案例研究,以验证DSML4ClinicalScore元模型,并展示如何在临床情况场景中使用该建议。
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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