Effective retrieval in Hospital Information Systems: the use of context in answering queries to Patient Discharge Summaries.
The move towards the electronic storage of medical records in Hospital Information Systems (HISs) presents significant challenges for AI retrieval techniques. In this paper, we argue that adequate information retrieval in such systems will have to rely on the exploitation of the conceptual knowledge in those records rather than superficial string searches. However, this course of action is dependent on the developments of natural language processing techniques and on retrieval systems that can exploit semantic/conceptual knowledge. We present a retrieval system, which attempts to realise the second of these developments. This system, called CONIR [developed in the context of the European Community project MENELAS (AIM 2023)] operates in the domain of Patient Discharge Summaries on coronary illness. CONIR uses flexible retrieval techniques, that exploit conceptual context information, over a database of elaborated semantic records. In the course of the paper we outline the sorts of knowledge structures that are required to do this type of retrieval and indicate how they are constructed.
Nangle
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B
Dept. of Computer Science, Trinity College, Dublin, Ireland.
Keane
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MT
D000043:Abstracting and Indexing; D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D006751:Hospital Information Systems; D006753:Hospital Records; D006801:Humans; D016247:Information Storage and Retrieval; D008962:Models, Theoretical; D009323:Natural Language Processing; D010351:Patient Discharge; D012660:Semantics; D012985:Software Design; D014584:User-Computer Interface