González Carolina, López Diego M, Blobel Bernd
Computational Intelligence Research Group, University of Cauca, Colombia.
Stud Health Technol Inform. 2013;189:44-9.
Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.
决策对于医疗保健领域的决策者而言是一项至关重要的任务，尤其是因为决策必须在不确定的情况下快速、准确地做出。鉴于提供高质量决策的重要性，在这一复杂过程中提供协助一直是人工智能有史以来面临的主要挑战之一。决策支持系统（DSS）因其在协助决策方面的有效性而在医学领域广受欢迎。从这个意义上说，已经开发了许多决策支持系统，但其中只有少数系统考虑对电子健康记录中包含的信息进行处理和分析，以便识别个体或群体的健康风险因素。本文探讨的是集成到电子健康记录系统（EHRS）或公共卫生信息系统（PHIS）中的智能决策支持系统。它分别为广泛的决策提供全面支持，旨在提高提供给患者的护理质量或公共卫生规划水平。
