Case-Based Reasoning in a Travel Medicine Application - Computational Intelligence in Healthcare: Advanced Methodologies - page 193

- Some Topic Agents require another Topic Agent's output as their input and
thus need to be queried successively, others can be queried at any time. In
order for the Coordination Agent to be able to obey these dependencies they
need to be indicated in the Knowledge Map in an easily comprehensible way.
- Based on the dependencies denoted in the Knowledge Map the agent needs
to be able to develop a request strategy on demand. This request strategy
should also be improvable with regard to different criteria such as the Topic
Agents' response speed, the quality of their information, the possible eco-
nomic cost of a request to a commercial information source and also possible
access limits.
- In order to guarantee the quality of the final result of the incremental re-
trieval process there needs to be a possibility to control what portion of the
result set is passed on to the subsequent Topic Agent. This portion should
be describable based on different criteria such as the number of cases or their
similarity.
- In order to allow for higher flexibility and a seamless inclusion in the
SEASALT architecture the functionalities need to be implemented in an
agent framework.
Firstly, in order for the Coordination Agent to be able to navigate the different
knowledge sources a format for the Knowledge Map had to be designed and
implemented. Since the dependencies between Topic Agents can take any form,
we decided to implement the Knowledge Map as a graph where each Topic Agent
is represented by a node and directed edges denote the dependencies. The case
attributes that serve as the next Topic Agent's input are associated with the
respective edges. The optimization criteria are indicated by a number between 0
(worst) and 100 (best) and are represented as node weights. In order to be able to
limit the portion of the result that is passed on to the next node we implemented
four possible thresholds, namely the total number of cases to be passed on, the
relative percentage of cases to be passed on, the minimum similarity of cases to
be passed on, the placement with regard to similarity of the cases to be passed
on (For instance the best and second best cases). An example graph from the
docQuery application can be seen in Fig. 4.
According to our example introduced in the beginning of this chapter the
region agent would return a case including the information that Alor and Bali
are Indonesian islands. Based on this information (i.e. Country = Indonesia)
queries for general safety information about this country, diseases that can be
contracted in the country, and certified (international standard) hospitals at
the destination are initiated. In this example there are two agents offering that
information: a free one 2 with information of lesser quality and a commercial
one 3 with information of higher quality. The retrieved diseases (Malaria, Yellow
Fever, Diphtheria, Tetanus, Hepatitis A, Typhoid Fever, etc.) are then subse-
quently used to query the medicaments agent for recommendable vaccinations
2 The cost 100 denotes a minimal price, that is 0,-.
3 The price is medium high, thus the cost value is 50, an agent with a higher cost
wouldhaveanevenlowercostvalue.