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

Authors: Sayda Umma Hamida; Narayan Ranjan Chakraborty

Addresses: Multidisciplinary Action Research (MARS) Lab, Daffodil International University, Dhaka, Bangladesh ' Multidisciplinary Action Research (MARS) Lab, Daffodil International University, Dhaka, Bangladesh

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.

Keywords: AI; mental health; anxiety; depression; PTSD; Chatbot.

DOI: 10.1504/IJMEI.2024.138290

International Journal of Medical Engineering and Informatics, 2024 Vol.16 No.3, pp.222 - 236

Received: 26 Jul 2021
Accepted: 11 Jan 2022
Published online: 01 May 2024 *

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