Expert System to Diagnose the Risk of Depression in the Elderly

Abstract

The objective of expert system development to diagnose the risk of depression in the elderly was to find the knowledge set to build a system of experts to find the risk of depression in the elderly. The result of the risk assessment results were analyzed from a survey of 2 query forms, and 8,320 sample data groups, with a procedure based on the study of data analysis and the creation of data tables to create the knowledge. The knowledge of the system in the form of If-then rules in the design process, which was a tree deciding to create a condition to diagnose the risk of 4 levels including normal, low, moderate, and severe level of ifthen rules. The total 786,433 rules by using mechanisms in the forward chaining for the risk diagnosis and that the rules were accurate of overall model as 98.85 percent, and in the development process, the If-then rules applied to develop the system with questions answered to the user, diagnosing risk and final operation of the system test and maintenance.