Show simple item record

dc.contributor.advisorJinan, Fiaidhi
dc.contributor.authorMariappan, Archana
dc.date.accessioned2023-05-24T20:33:55Z
dc.date.available2023-05-24T20:33:55Z
dc.date.created2023
dc.date.issued2023
dc.identifier.urihttps://knowledgecommons.lakeheadu.ca/handle/2453/5158
dc.description.abstractWorld 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. The majority of individuals don’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. 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 preliminary identification of mental health problem in the user by identifying and providing level-I therapeutical support for depression by employing conversational AI.Thisresearch utilizes technologies like Artificial Intelligence and its subfield Natural Language Processing (NLP) to provide an amicable environment for the user 24/7 and it can be integrated in cross platforms like iOS, android and windows etc. A knowledge base retrieval flow network is created with data which is stored globally through which the data is retrieved at the faster rate. After the user enters the chatbot they can converse with the bot initially else he/she also has the option of taking the assessment directly after entering the bot. Behind this process, sentiment analysis takes place which classifies the text into positive, negative or neutral. Once the score exceeds the range it was initially set then it will give the result accordingly. The dataset used in this study is AFINN-en-165 which already has pretrained list of words with the score. The program employed in the entire system is written through Flutter framework. 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.en_US
dc.language.isoen_USen_US
dc.subjectMental illnessen_US
dc.subjectMental health chatboten_US
dc.subjectConversational AIen_US
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectDepression (therapeutical support)en_US
dc.subjectDigital psychiatryen_US
dc.titlePreliminary identification and therapeutic support of depression in mental health using conversational AIen_US
dc.typeThesisen_US
etd.degree.nameMaster of Scienceen_US
etd.degree.levelMasteren_US
etd.degree.disciplineComputer Scienceen_US
etd.degree.grantorLakehead Universityen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record