Effectiveness of machine learning for mental health: observing the mental state of Bangladeshi people

dc.contributor.authorHamida, Sayda Umma
dc.contributor.authorChakraborty, Narayan Ranjan
dc.date.accessioned2025-11-16T05:50:29Z
dc.date.available2025-11-16T05:50:29Z
dc.date.issued2024
dc.descriptionArticle
dc.description.abstractAnalysing and finding the most used AI applications in the mental health sector and advising appropriate directions for advanced research is the intention of this research. With this purpose, authors commenced a systematic review by analysing selected 31 articles and found several neuroimaging and recognising technologies in real life for checking brain abnormalities. Besides, it revealed from the study that bot is the most used AI assistant in digital care. However, the authors surveyed the young people (aged between 19-29) of Bangladesh to identify mental disorders like as: anxiety, depression, and PTSD. The authors used Python to analyse the dataset, find correlations, and applied machine learning classification algorithms (e.g., decision tree, support vector machine, and random forest) to measure the accuracy. The researchers explained a few threats of mental instability in their findings and offered several directions for future research using virtual and real-life AI technologies.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/15645
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/15645
dc.language.isoen_US
dc.publisherScopus
dc.sourceDIU Institutional Repository
dc.subjectAI,
dc.subjectmental health,
dc.subjectanxiety,
dc.subjectdepression,
dc.subjectPTSD,
dc.subjectChatbo
dc.titleEffectiveness of machine learning for mental health: observing the mental state of Bangladeshi people
dc.typeArticle

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