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

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dc.contributor.author Hamida, Sayda Umma
dc.contributor.author Chakraborty, Narayan Ranjan
dc.date.accessioned 2025-11-16T05:50:29Z
dc.date.available 2025-11-16T05:50:29Z
dc.date.issued 2024
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/15645
dc.description Article en_US
dc.description.abstract Analysing 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. en_US
dc.language.iso en_US en_US
dc.publisher Scopus en_US
dc.subject AI, en_US
dc.subject mental health, en_US
dc.subject anxiety, en_US
dc.subject depression, en_US
dc.subject PTSD, en_US
dc.subject Chatbo en_US
dc.title Effectiveness of machine learning for mental health: observing the mental state of Bangladeshi people en_US
dc.type Article en_US


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