DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded
Depressive disorder is an illness that involves the body, mood and thoughts. It interferes with daily life, normal functioning and causes pain for both the person with the disorder and those who care about him/her. Severe depression may lead to serious illness or suicide. The most affected sector is the Adolescent Community. The biggest problem in diagnosing and treating depressive disorders is recognizing that someone is suffering from it. As various factors are involved, it is very difficult for the Psychologists to diagnose depressive disorders correctly at an early stage itself. Nowadays, computers are used in assisting Physicians to diagnose diseases and identify correct treatments according to the patient details. In the same way, computers can also be used in assisting psychologists to diagnose mental disorders and identify correct treatments according to the patient details. Various techniques are available to store the expert knowledge and computerize the diagnosis process. Bayesian Network is such a technique that combines statistics and expert knowledge to diagnose diseases effectively. This paper proposes a Framework for diagnosing depression level in adolescents using Bayesian Networks. Initially, Ontology should be constructed to provide a basis for Bayesian Networks. The ontology acts as the topology and shows the relationships between adolescent depression concepts. By applying probabilities to the relationships between concepts from the statistics, and by using Bayes Theorem, depression level of a patient can be diagnosed effectively. This framework may help novice psychologists to understand the domain concepts and also to diagnose the depression level and suggest correct treatments.
