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CBR in Medicine
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Lothar Gierl4  , Mathias Bull4 and Rainer Schmidt4
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Dept. for Medical Informatics and Biometry, University of Rostock, Rembrandtstrasse 16/17, D-18055 Rostock, Germany |
Abstract
Medicine differs from other knowledge domains by the interaction of research and practice. The objects are the patients -
very complex organisms with high biological variance and a lot of interactive vital processes. The knowledge of these processes
and their interactions is often weak. It mostly depends on a high number of sometimes even contradicting signs and symptoms.
Furthermore, the individual vital processes are affected by changes of the environmental situations (e.g., new resistances,
diseases or pathogens). To discover new medical knowledge, traditional research is based on disease case descriptions, case
collections, and biostatistical case studies.
In contrast to other knowledge domains, clinical practice is characterized by a professional documentation of cases. Numerous
case collections have been accumulated.
On the one hand, knowledge of special topics is often highly centralized. This means that only one person is an expert in
this field, such as antibiotic therapy. On the other hand, medical knowledge in different clinics is distributed in specialists
and knowledge sources such as patient oriented documents, medical journals, data bases, text work, etc.
Physicians are overwhelmed by the amount of data, even for one patient (e.g., hundreds of parameter values from clinical chemistry,
dozens of images from radiology, sonography, etc., and dozens of textual documents). Physicians are usually confronted with
contradicting information. For instance, laboratory parameters and clinical features may contradict. Moreover, they have to
cope with vague data, e.g., complaints of a patient.
Clinicians mostly work under stress. This means, they have to choose rapidly from a large number of alternatives. For instance,
they have to decide for an appropriate dosage of a selection of drugs in order to preserve a desired impact for a particular
disease.
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