Computer Science Department Thesis Defense - Archana Mariappan

Please join the Computer Science Department for the upcoming thesis defense:

Presenter: Archana Mariappan

Thesis title: Diagnosis and Level-I Therapeutical Support of Depression in Mental Health using Conversational AI


Abstract: World Health Organization statistics indicate that one out of every eight people suffers from mental illness. Due to the fear of stigma and social discrimination, they start being resilient and end up going through difficult situations alone. They fear criticism and start isolating them from friends, family and neighbours. They fear that may be called as ‘crazy’ which may affect their education, career and daily lives in a negative manner. Mostly people aren’t much aware about the mental health illness which may lead them into complicated consequences. Also, most of the people lack the knowledge about the mental health issues and trying to solve it alone without knowing the complexity of the future problems related to it. Also, people find it difficult to open up about their personal information and feelings to a stranger or counsellor assuming that their data wouldn’t be confidential. The majority of individuals doesn’t have access to effective care. If the issue isn’t treated with care it can lead to serious mental problems such as it may cause depression, obsessive compulsive disorder, anxious or personality disorder. Literally, majority of the population have inadequate knowledge about the mental health illness. In order to overcome this problem, our mental health chatbot was created. Our study aims to provide efficient and essential care to the people with mental health concerns according to their needs and supplying the basic information regarding mental health problems through various sources. The proposed system eases the diagnosis of mental health problem in the user by identifying and providing level-I therapeutical support for depression by employing conversational AI. This paper utilizes technologies like Artificial Intelligence and its subfield Natural Language Processing (NLP) to provide a amicable environment for the user 24/7 and it can be integrated in cross platforms like iOS, android and windows etc. This system allows the users to schedule appointment, to learn in detail about the terminologies of mental health and it provides resources for feel good activities like videos and music. Through this system they can candidly express their feelings to the conversational AI chatbot besides their insecurity. The Artificial Intelligence (AI) in turn provides them with chat support, acts as a bridge to understand the situations and suggests solutions depending on the level of mental health deterioration. We propose a fully automated and powerful first-level detection and support system for mental health.


Committee Members:
Dr. Jinan Fiaidhi (supervisor, committee chair), Dr. Sabah Mohammed, Dr. Carlos Zerpa (Kinesiology)

Please contact grad.compsci@lakeheadu.ca for the Zoom link.
Everyone is welcome.