Literature review assesses suicide risk and prevention strategies, suggesting data mining and machine learning techniques could help.
Suicide is the act of taking own life purposefully. Suicide trail aims at harming oneself with mortal intention. The behavior of the people committing suicide can be analyzed over a range of activities like thinking, setting up and committing suicide. Global study says that the second major cause for deaths today is suicide. Nearly, 71% of the deaths in women and 50% of the deaths in men these days are because of suicides. In some countries, the highest suicide rate found among the people aged above 70 years and in some countries it is more among the teenagers aged between 15 and 29. Suicidal behavior indicates deep unhappiness and sometimes mental disorder. Both factors are not necessarily dependent on each other. The objective of this study is to present the literature review on suicidal risk assessment and prevention mechanisms proposed by different researchers using data mining and machine learning techniques to minimize the suicidal rate.
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Saka et al. (2019) studied this question.
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