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Mental Health Analysis During Pandemic: A Survey of Detection and Treatment
Conference proceeding   Peer reviewed

Mental Health Analysis During Pandemic: A Survey of Detection and Treatment

Paramita Basak Upama, Maria Valero, Hossain Shahriar, Mohammad Syam and Sheikh Iqbal Ahamed
2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), Vol.2023-, pp.1530-1538
Annual Computers, Software, and Applications Conference (COMPSAC), 47th (Torino, Italy, 06/26/2023–06/30/2023)
08/2023
DOI: https://doi.org/10.1109/COMPSAC57700.2023.00236
Web of Science ID: WOS:001046484100226

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Abstract

COVID-19 Pandemics Quantum computing quantum machine learning remote healthcare Artificial Intelligence or Cybernetics Machine Learning Mental Health Mental Health Services Telemedicine
In the ongoing pandemic of COVID-19, the entire population of the world is getting affected either physically or mentally. In terms of physical diseases, the symptoms and treatments are more known, and people tend to be more aware of them. But the mental health is frequently ignored by general people, which has worsened during the pandemic. Though several research were conducted to cope with mental health analysis, detection and treatment in this current pandemic situation, the practical implementation are few. Among them the optimal results are produced by the ones adapting artificial intelligence (AI). Also, remote healthcare services have provided their supportive hands to combat the situation. In this paper, a systematic review of the use of AI and remote healthcare services has been conducted, which focuses on the detection, analysis and treatment of mental health among people during the COVID-19 pandemic. The current essence, challenges and limitations have also been discussed here. After evaluating the methods of data collection, usefulness and efficiency of the available works in symptom detection remotely and correctly, and data analysis algorithms used by them- a recommendation was made on the open research scopes in this field.

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