Abstract:
The topic of drug interactions has received
great attention worldwide recently. If a drug is not
administered in appropriate quantity with an appropriate
combination of the drug with drug or other substances, the
result will be a high risk of dangerous interactions which
lead to potentially harmful side effects which are ranging
from treatment failure, economic degradation, and death
due to lack of drug information and maladministration of
drugs among health professionals. Thus, this study was
initiated with the main aim to develop a self-learning
knowledge-based system to mitigate the impact of drug
interactions. To develop this system, design science
methodology with the integration of knowledge
engineering method was used; and semi-structured
interview, document analysis to acquire knowledge;
questionnaire to grasp users‟ feedback, and purposive
sampling technique to select domain experts were used.
The acquired knowledge was then represented using a
production rule and modelled using a decision tree. The
system was implemented using PROLOG on
SWI-PROLOG editor and evaluated using system
performance and user acceptance testing. The developed
system was evaluated and 96% of the users were satisfied.
As well as the performance of the system was evaluated
and recorded 80% accuracy, thus it can be concluded that
the system achieves good performance. However, in order
to make the system fully applicable in the domain area,
further research work to incorporate adequate knowledge,
develop online knowledge-based systems and mobile
applications were recommended to enhance the
accessibility of the developed system
