Hashmi Zafar Iqbal, Abidi Syed Sibte Raza, Cheah Yu N
Health Informatics Research Group, School of Computer Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia.
Stud Health Technol Inform. 2002;90:601-5.
Initiatives in healthcare knowledge management have provided some interesting solutions for the implementation of large-scale information repositories vis-à-vis the implementation of Healthcare Enterprise Memories (HEM). In this paper, we present an agent-based Intelligent Healthcare Information Assistant (IHIA) for dynamic information gathering, filtering and adaptation from a HEM comprising an amalgamation of (i) databases storing empirical knowledge, (ii) case-bases storing experiential knowledge, (iii) scenario-bases storing tacit knowledge and (iv) document-bases storing explicit knowledge. The featured work leverages intelligent agents and medical ontologies for autonomous HEM-wide navigation, approximate content matching, inter- and intra-repositories content correlation and information adaptation to meet the user's information request. We anticipate that the use of IHIA will empower healthcare stakeholders to actively communicate with an 'information/knowledge-rich' HEM and will be able to retrieve with ease 'useful' task-specific information via the presentation of cognitively intuitive queries.
医疗保健知识管理方面的举措为大规模信息库的实施提供了一些有趣的解决方案，相对于医疗保健企业记忆（HEM）的实施而言。在本文中，我们提出了一种基于智能体的智能医疗保健信息助手（IHIA），用于从一个由以下部分融合而成的HEM中进行动态信息收集、筛选和适配：（i）存储经验知识的数据库，（ii）存储经验知识的案例库，（iii）存储隐性知识的情景库，以及（iv）存储显性知识的文档库。这项特色工作利用智能体和医学本体进行全HEM范围的自主导航、近似内容匹配、库间和库内内容关联以及信息适配，以满足用户的信息请求。我们预计，IHIA的使用将使医疗保健利益相关者能够与“信息/知识丰富”的HEM进行积极沟通，并能够通过呈现认知直观的查询轻松检索到“有用的”特定任务信息。
