Authors :
Mansi Chandra; Dr Shruthi SD
Volume/Issue :
Volume 8 - 2023, Issue 11 - November
Google Scholar :
https://tinyurl.com/7j73ud5j
Scribd :
https://tinyurl.com/4vfjpvum
DOI :
https://doi.org/10.5281/zenodo.10082521
Abstract :
In today's fast-paced world, mental health
concerns that include anxiety, depression, and stress have
become quite frequent among individuals of all ages. One
of the major reasons behind this problem is the lack of
awareness among the masses. Mental health refers to
one's psychological, emotional, and social well-being, and
it is essential at all stages of life, from childhood and
adolescence to maturity. In this study, machine learning
algorithms were used to predict anxiety, Depression, and
stress. To apply the machine learning algorithms,
information was gathered from people of different ages,
occupations, sexes, and lifestyles through a questionnaire
with questions psychologists frequently use to
comprehend their patients' issues in specifics. The results
reveal that the model has a high level of accuracy in
predicting mental health outcomes.
Our aim with this paper is to raise awareness and
make people aware that they may be suffering from
mental health disorders like Anxiety, Depression, and
Stress. The model developed in this study can assist
healthcare providers in identifying patients at high risk of
developing Mental issues and can enable early
intervention and prevention strategies. We believe
establishing such a system into effect could help us avoid
a future "Mental health epidemic" and make diagnosis
easier for people.
Keywords :
Anxiety, Depression, Decision Tree Algorithm, Mental Health Prediction, Machine Learning, Stress.
In today's fast-paced world, mental health
concerns that include anxiety, depression, and stress have
become quite frequent among individuals of all ages. One
of the major reasons behind this problem is the lack of
awareness among the masses. Mental health refers to
one's psychological, emotional, and social well-being, and
it is essential at all stages of life, from childhood and
adolescence to maturity. In this study, machine learning
algorithms were used to predict anxiety, Depression, and
stress. To apply the machine learning algorithms,
information was gathered from people of different ages,
occupations, sexes, and lifestyles through a questionnaire
with questions psychologists frequently use to
comprehend their patients' issues in specifics. The results
reveal that the model has a high level of accuracy in
predicting mental health outcomes.
Our aim with this paper is to raise awareness and
make people aware that they may be suffering from
mental health disorders like Anxiety, Depression, and
Stress. The model developed in this study can assist
healthcare providers in identifying patients at high risk of
developing Mental issues and can enable early
intervention and prevention strategies. We believe
establishing such a system into effect could help us avoid
a future "Mental health epidemic" and make diagnosis
easier for people.
Keywords :
Anxiety, Depression, Decision Tree Algorithm, Mental Health Prediction, Machine Learning, Stress.
