Suicidal Tendency Detection Using Machine Learning

AUTHOR(S)

B.Channarayapriya, P.Suresh kumar Reddy

DOI: https://doi.org/10.46647/ijetms.2023.v07i05.002

ABSTRACT
Suicidal Tendency or the intension to kill oneself or end one’s life is a catastrophic situation which is mostly unknown by any person in the victim’s life. Suicide has been an intractable public health problem despite advances in the diagnosis and treatment of major mental disorders. In many studies it is clearly evident that, victims tend to kill themselves either to end their pain or pressure or to have a sense of relief that they are not going to live in this world anymore. This project aims to propose a method that helps the family, friends or the close ones of the victim to immediately detect if the person has already started feeling the sense of depression. The main aim is to find a strong co-relation between components in the subsystem and compare the accuracies to build an alarming system. “Better late than never” the victim can be saved by the proposed method and immediate treatment can be started. Unlike the existing systems, this project aims to detect the suicidal tendencies in multiple aspects instead of focusing on a single perspective.

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How to Cite This Article:
B.Channarayapriya, P.Suresh kumar Reddy . Suicidal Tendency Detection Using Machine Learning . ijetms;7(5):11-20. DOI: 10.46647/ijetms.2023.v07i05.002