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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM16332
Volume:
6 |
9 |
Sep 2022
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Today’s culture has a significant problem with suicide. To save lives, it must be a primary focus to identify and stop suicide attempts as early as possible. For identification system related to online media web, suicide attempts tracking (SID) strategies currently used feature technology or deep learning procedures in machine learning, as well as medical trials depending on encounter among caseworkers or experts and the focused individual people. The approaches in these areas are completely introduced and discussed in this survey for the first time. Based on their data sources, which include surveys, Domain-specific SID programs, suicide notes, patient records, and virtual user content are evaluated. To facilitate future research, a number of particular initiatives and database is built and described. Lastly, we highlight the flaws in the prior projects and offer an alternative strategy.
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Publication Date
10/8/2022
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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