Suicide Rate and Factors Analysis: Pre and Post COVID Pandemic Data Analysis
2022 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-1948790
ABSTRACT
According to the 2021 Report from the World Health Organization (WHO), more than 700,000 people have taken their life. Suicide can be prevented but so far most of the efforts to do so have fallen short. However, the use of machine learning and artificial intelligence offers new opportunities to increase the accuracy level of prediction and aid the goal of suicide prevention. This paper reviews literature concerning the machine learning methods used to help identify various risk factors and help prevent suicide. This paper also presents our research and analysis findings which were used to identify various suicide risk factors and additional analysis of whether there are any correlations or variations in the risk factors from pre-and post-pandemic datasets regarding suicide rates. This is especially important during times of high stress, such as a worldwide pandemic and quarantine. The dataset(s) obtained from WHO suggest that high levels of risk factor identification are possible and This paper and the analysis serve as supporting research and guide to aid in the continued ambitious goal of suicide prevention worldwide © 2022 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Topics:
Long Covid
Language:
English
Journal:
2022 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2022
Year:
2022
Document Type:
Article
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