Literature Review on Self-Harm and Suicidal Tendencies using Machine Learning Technology

Abstract

As per W.H.O, nearly 793,000 individuals passed away in 2016 due to suicidal and self-harm tendencies which is approximately one individual every 40 seconds. It is a global phenomenon and occurs throughout the lifespan. There are suggestions that for every adult who was deceased by suicide there might have been more than 20 others attempting suicide. Although effective treatment is known for self-Harm and suicidal tendencies, it is not accessible to the majority of sufferers in both wealthy and poor nations. In this aspect, many scientific discipline and researchers have been working on machine learning models to determine the stage of self-harm and suicidal tendencies. This paper presents contextual knowledge on self-harm and suicidal tendencies and practice of machine learning and also evaluation of past studies that apply machine learning for determining self-harm and suicidal tendencies with their features.