A graph-grammar approach to represent causal, temporal and other contexts in an oncological patient record

The data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-s...

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Bibliographic Details
Published in:Methods of information in medicine Vol. 35; no. 2; p. 127
Main Authors: Müller, R, Thews, O, Rohrbach, C, Sergl, M, Pommerening, K
Format: Journal Article
Language:English
Published: Germany 01.06.1996
Subjects:
Adverse Drug Reaction Reporting Systems
Artificial Intelligence
Child
Computer Graphics
Decision Support Techniques
Documentation - methods
Expert Systems
Humans
Information Storage and Retrieval
Medical Records Systems, Computerized
Neoplasms - therapy
Software
Therapy, Computer-Assisted
Vocabulary, Controlled
ISSN:0026-1270
Online Access:Get more information
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Summary:The data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (Therapy Management in Pediatric Oncology), which supports therapy and monitoring in pediatric oncology, a graph-grammar approach has been used to design and implement a graph-oriented patient model which allows the representation of non-trivial (causal, temporal, etc.) clinical contexts. For context acquisition a mouse-based tool has been developed allowing the physician to specify contexts in a comfortable graphical manner. Furthermore, the retrieval of contexts is realized with graphical tools as well.
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ISSN:0026-1270
DOI:10.1055/s-0038-1634641