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Employee health prediction

The significance of mental health in reaching global sustainable development goals has come under more and more scrutiny in recent years. Different circumstances, including disease, can have an impact on a person's emotions, thoughts, attitude, and decision-making. Due to stress at work, mental problems are becoming increasingly prevalent among employees. Personality disorders, anxiety disorders, phobias, psychotic disorders, depression, mood disorders, eating disorders, and a few others can be brought on by mental disease. In this study, we investigated the root causes of mental illnesses in the workforce using data from the Open Sourcing Mental Illness (OSMI) Mental Health in Tech Survey. Here, we used machine learning algorithms to analyse the severity of mental illness for working employees based on various factors or attributes, such as self-employment, mental health history in the employee's family, company offering beneficial health effects, whether the employee is in treatment for mental illness, and much more. The primary goal of such data analysis is to raise public awareness of mental illness in the workplace, which aids in reducing the issues associated with mental diseases. In order to prevent any tragic events brought on by numerous variables in a working environment, this document supports and provides advice regarding the causes of serious mental health behaviours. As a result, this gives an estimate of how employees in tech and non-tech organisations are impacted. This analysis helps us reach a conclusion that addresses the issues of whether location, the number of employees at a company, and whether or not mental health is taken into account, as well as how these external elements affect one's mental and physical well-being in the working sectors. final year project is based on IEEE Paper.this will be one of the best Final year engineering project for computer science. Components that we will provide are.
1.complete documentation support
2.complete working hardware/software implemented in students environment 3.classes will held accordingly.

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