Expert System to Diagnose Mental Health Disorders Using the Dempster Shafer Algorithm
Abstract
This study aims to address the challenge of diagnosing mental disorders by using an expert system to provide accurate and efficient diagnosis. Mental health is crucial for achieving harmony in life, and the ability to face problems, feel happiness, and maintain positivity are all essential aspects of this. However, diagnosing mental disorders can be difficult and time-consuming, as symptoms may vary depending on the patient's condition and lifestyle. The study utilizes symptom data from 30 patients with 6 types of mental disorders, with each symptom assigned a weighted value of belief for the corresponding disorder. The Dempster Shafer algorithm is then used to process this data and obtain a total confidence value for each disorder. The results show a 97% confidence value for the patient's mental disorder, which can help psychologists make informed decisions and provide appropriate treatment.
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