2 KNOWLEDGE DOMAINS
The human expert knowledge is subdivided into four
super classes of knowledge domains:
The patient situation includes all personal data
including his history with all past diseases and his
actual health state. In this situation the patient
related best IOL-implant has to be found. But a lot
of intraocular lenses are available, different in
functionality, form, material, haptics, design, and
refraction power values. To select the best option for
the patient is not trivial.
Additionally, many clinical measurement and
diagnostic methods are available and are applied in
the preoperative situation of the human being. Some
measured values can be wrong when for instance
past diseases are not known.
An additional knowledge domain is the wide
field of the different surgical techniques. The
application of these methods depends also on the
patient situation, the designed IOL, and the
determined diagnostics. This complexity yields a
computer-based structuring of the knowledge to
support the surgeons by logical reasoning including
the explanation of the reasoning process (Figure 2).
These four domains (patient’s situation,
diagnostics, IOL types, and the surgical techniques)
correlate among each other, so the dependencies are
very complex and they are no longer linear. A
formalized description of the different knowledge
domains must be performed. They should be
regarded before the final selection of the IOL and
the implantation at the real patient is done. The
elements of the knowledge domains and the
correlations between them are represented as a
semantic net with predicates, i.e., the ontology. This
structure, especially in combination with an efficient
visualisation is a very important help for the
surgeons.
Figure 2: The different knowledge domains.
3 SYSTEM ARCHITECTURE
A knowledge-based approach is well suited to make
available as well the human expertise as the
background deep knowledge to map the logical
reasoning process to computer software (Studer et
al., 1988). So, the need is to find out formal
structures to manage the different knowledge
domains. The knowledge-based support system is
conceptualized and realized in different semantic
layers:
Figure 3: Layer based architecture of the system.
On the basic layer L1, a frame-based information
system is performed with all features of the different
ontologies. The descriptive layer for the interested
information categories is a hierarchical class –
subclass system with a refinement process and
special specification from class to subclass. An
ontology concept consists of the declarative part of
the semantics, the meaning in this knowledge-based
approach, the sources (publications, authors and so
on), and multimedia representations (pictures, tables,
movies) (Benjamin et al., 1998).
On the layer L2, the concept of the semantic
dependencies is subdivided into different types of
relations (predicates), based on natural language.
The knowledge elements of layer L1 can be
correlated by so called weak links, that means
semantic associations between the different items.
They are used to generate a suggestion for the
surgeon, also to consider the semantic neighboured
knowledge domain when regarding a first one. The
surgeon can be guided from one interest of point to
the next in an intelligent manner. An additional type
of relation is performed by a stronger relation like a
rule in a rule-based expert system. If the premises of
the first domain are given, then the second
knowledge items result as conclusion from the
preconditions.
Based on the static description of the concepts in
L1 including their correlations in L2 the reasoning
process in layer L3 depends on the different
OP methods
patient
diagnostics
IOL types
L1: frames of the domains:
IOL types, surgical methods,
diagnostics, patient situation
L2: correlations, dependencies
L3: knowledge processing and reasoning
L4: user interface, explanation, acquisition
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