Developing A Learning Knowledge-Based System For Diagnosis And Treatment Of Malaria
Malaria is a disease that significantly affects the poor
who suffer economic, social and educational
deprivation. Malaria is accountable for between 1.5
and 2.7 million deaths worldwide each year and at
least 30% of all malaria deaths take place in complex
emergencies. This is because of shortage of
professionals and scarcity of laboratory equipment,
especially in developing countries.In the efforts to
address such problems, it is important to develop
Knowledge-based system (KBS) that can provide
support for health professionals and patients to
facilitate diagnosis and treatment of malaria
patients.However, it does not update the knowledge
once it is developed without the involvement of
knowledge engineer. The aim of this research was
developing learning knowledge based system for
diagnosis and treatment of malaria.Knowledge
Engineering research design was used to developed
prototype system. Purposive sampling technique was
used to select domain experts for knowledge
acquisition. The knowledge was acquired using
both structured and unstructured interviews from
domain experts and represented by production rule.
Developing the system in local languages, improving
the user interface and applying other techniques are
the future works of the study.
Keywords: Malaria, Knowledge Based System,
Knowledge Engineering, Rule based systemMalaria is a disease that significantly affects the poor
who suffer economic, social and educational
deprivation. Malaria is accountable for between 1.5
and 2.7 million deaths worldwide each year and at
least 30% of all malaria deaths take place in complex
emergencies. This is because of shortage of
professionals and scarcity of laboratory equipment,
especially in developing countries.In the efforts to
address such problems, it is important to develop
Knowledge-based system (KBS) that can provide
support for health professionals and patients to
facilitate diagnosis and treatment of malaria
patients.However, it does not update the knowledge
once it is developed without the involvement of
knowledge engineer. The aim of this research was
developing learning knowledge based system for
diagnosis and treatment of malaria.Knowledge
Engineering research design was used to developed
prototype system. Purposive sampling technique was
used to select domain experts for knowledge
acquisition. The knowledge was acquired using
both structured and unstructured interviews from
domain experts and represented by production rule.
Developing the system in local languages, improving
the user interface and applying other techniques are
the future works of the study.
Keywords: Malaria, Knowledge Based System, Knowledge Engineering, Rule based system
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ABOUT THE AUTHORS
Chala Diriba
Lecturer
Million Meshesha
Lecturer
Debela Tesfaye
Lecturer
Chala Diriba
Lecturer
Million Meshesha
Lecturer
Debela Tesfaye
Lecturer