Case-Based Reasoning in a Travel Medicine Application - Computational Intelligence in Healthcare: Advanced Methodologies - page 184

docQuery is the core application and supports establishing a community to ex-
change experiences. Furthermore the users are involved in advancing the knowl-
edge provided by docQuery and influence which issues are raised by sending
requests, giving feedback and sharing experiences. docQuery is supposed to be
a non-profit project and will provide travel medical information, prevention and
preparation free of charge.

3 4R Cycle from the Travel Medical Point of View

CBR is a methodology based on Schank's theory [2] on the transfer of the func-
tion of human behavior onto computational intelligence. The main idea describes
how people's experiences (or parts of the experiences) are remembered and later
reconsidered when facing new and similar problems, reusing or adapting the pre-
vious solution in order to solve new problems. In CBR a case is described as a
problem and its according solution.
In comparison to other methodologies like logical programming, CBR can deal
with incomplete information and the domain does not have to be completely
covered by a knowledge model before a system can be built. The integrated
learning process allows a CBR system to learn while it is used. Based on Schank's
ideas Aamodt and Plaza [1] introduced the Retrieve-Reuse-Revise-Retain (4R)
process cycle that is until today the reference model for CBR applications.
Today there are three major types of CBR systems: Textual CBR systems [3]
that basically deals with textual cases and combine Natural Language Process-
ing Techniques with the CBR approach. Conversational CBR applications with
are characterized by subsequent retrieval steps that narrow down the possible
solution by iteratively setting attributes and the most often applied approach of
Structural CBR which features a strict case representation and various retrieval
techniques. Today many applications combine those approaches according to the
given system requirements. A more detailed description of the CBR approaches
and their application domains is discussed by Bergmann [4].
Although not all applications implement each process, most CBR systems
are based on this model. To describe the 4R cycle, we will again use the travel
medicine example presented in section 2.2 and illustrate the 4R example in
Figure 1.
The current situation is a family plans that to spend their Easter holidays
in Alor and Bali. This is the problem description that has to be transfered in
the problem representation to initiate a retrieval request. Within this example
we are only looking for vaccination suggestions. To enable an ecient retrieval
different case base indexing structures have been developed and each of them
addresses special features of a CBR type. Before a retrieval can be executed the
problem has to be analyzed so an similarity-based retrieval within the case base
can be executed.
The case base or knowledge base contains previous cases as well as background
knowledge, this can be rules to either complete requests (enriched with tags) or
modify solutions, or similarity measures to compute the similarity between two