|Title:||PROTOTYPE KNOWLEDGE BASED SYSTEM FOR ANXIETY MENTAL DISORDER DIAGNOSIS|
|???metadata.dc.contributor.*???:||Dr. Gashaw Kebede|
|Abstract:||Mental health is the basic building block for the entire healthy life of a person. There is a motto which explains the significance of mental health as “Without mental health no health!” Mental health problems touch every aspects of human life such as humans’ general health condition, work, family life, social relations, etc. However, mental health issue is one of the neglected issues throughout the world. Particularly, in developing countries, mental health has the least attention it deserves. Ethiopia is one of the developing countries. In Ethiopia, mental health issue is not getting sufficient attentions. The major challenge for mental health service in the country is shortage of skilled mental health professionals. In Ethiopia, the number of mental disorder patients and mental health professionals are disproportionate too. Due to this the distribution of mental health professionals is greatly unfair. Lacks of knowledge among primary health care workers, the allocation of insufficient budgets for mental health issue, and the absence of adequate awareness about mental illnesses are the other challenges that are creating obstacles to address mental health services satisfactorily. In an attempt to address such problems, the objective of this research work is to look into the possibility of applying knowledge based systems technology to diagnose patients with anxiety mental disorders by developing prototype knowledge based system that can mimic /simulate the services of psychiatrists and psychologists. To achieve this objective, knowledge is acquired using both structured and unstructured extensive interviews with three experts, which are selected purposively from Amanuel Mental Specialized Hospital and Rank Higher Clinic. Additionally, knowledge is acquired from secondary sources by using document analysis method of knowledge elicitation. The knowledge acquired is modelled using decision tree structure that represents concepts, parameters and procedures involved in anxiety disorders diagnoses. Based on the model, the prototype is developed with SWI Prolog by using ‘if – then’ rules. The prototype developed uses backward chaining to infer the rules and extract conclusions and recommendations. XI Domain experts evaluate the prototype and satisfactory result is found; about 86% of system evaluators accept the prototype. Additionally, the performance of the system is evaluated by using predictive validation technique with twenty test cases. The result of the validation revealed the accuracy of the prototype to be 85%. The prototype knowledge based system needs further studies to expand its scope and to enhance the performance of it by integrating with other knowledge representation techniques.|
|Description:||A Thesis Submitted to the School of Graduate Studies of Addis Ababa University in Partial Fulfilment of the Requirements for the Degree of Master of Science in Information Science|
|Appears in Collections:||Thesis - Information Science|
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