Friday 19th of April 2024
 

Developing A Learning Knowledge-Based System For Diagnosis And Treatment Of Malaria


Chala Diriba, Million Meshesha and Debela Tesfaye

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


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