Guidi G, Pettenati M C, Miniati R, Iadanza E
Department of Electronics and Telecommunications, University of Florence, Florence, Italy.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:2210-3. doi: 10.1109/EMBC.2012.6346401.
In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
在本文中，我们描述了一个心力衰竭分析仪表盘，它与一个用于自动获取一组患者临床参数的便捷设备相结合，可支持远程监测功能。该仪表盘的智能核心是一个计算机决策支持系统，旨在协助非专科护理人员的临床决策，它基于三个功能部分：诊断、预后和随访管理。比较了四种基于人工智能的技术来提供诊断功能：神经网络、支持向量机、分类树和一个由遗传算法生成规则的模糊专家系统。使用了最先进的算法来支持基于评分的预后功能。患者的随访用于完善诊断。
