Abstract
As the world progresses, technology plays an increasingly important role. This has resulted in a massive increase in work prospects for individuals all around the world. However, it also comes with a busy schedule that has a negative impact on people’s mental health. However, gathering data and manually going through it one by one, as well as treating individuals who are suffering from it once the correct number of people has been determined, will be a challenging job for a person as well; there may be inaccuracies when going through data, and it will take a long time. To solve this challenge, a better method is needed that can save human effort and time while still forecasting the correct measure, this is where machine learning comes into role. Machine learning algorithms are more accurate, timely, automated data processing, cost saving and reliable toward the mental health practices and the clinical decisions. So, in this chapter, authors have focused on the machine learning algorithms to assess the mental health of the tech employees. We used different machine learning algorithms to create the most accurate predictions and work appropriately to perform curative measures of mental health of an individual.
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Mittal, M., Usharani, B., Harish, Manish (2022). Measuring Mental Health at Workplaces Using Machine Learning Techniques. In: Mittal, M., Goyal, L.M. (eds) Predictive Analytics of Psychological Disorders in Healthcare. Lecture Notes on Data Engineering and Communications Technologies, vol 128. Springer, Singapore. https://doi.org/10.1007/978-981-19-1724-0_8
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