What is it about?

Nowadays the human-being is suffering from many issues in the society. In the current situation mental health problem is a prevalence issue. Usage of sensor data and dataset is an interesting issue dealing with prediction of mental health of the people living in society. The data science process can be carried out by collecting datasets from various health sector domains and differentiated into three categories such as low, medium, high. This is helpful in detecting weather the person is suffering from any mental issue or not. A sample test is conducted to assess the health conditions of healthy groups and people having mental illness with the help of data mining in data science field. This paper explains about a novel framework for prediction of public mental health condition which are helpful to handle the challenges in the field of data science. Evaluation of data science surveys is different from traditional data analysis due to the scientific approach method used during data classification and filtration. Here the role of "Data Science" framework is for promoting the usage of framework by the healthcare professionals to face challenges of mental health.

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Why is it important?

Mental health problems have become increasingly prevalent in society, affecting individuals across various demographics. By focusing on prediction and detection using sensor data and datasets, this information acknowledges the urgency of addressing mental health concerns and the potential of data-driven approaches to mitigate them. The integration of data science methodologies into mental health prediction demonstrates the application of advanced technologies for societal benefit. By leveraging sensor data and datasets, data science can provide insights into mental health conditions, potentially leading to early intervention and improved outcomes for affected individuals.

Perspectives

The data science process involves categorizing datasets into three categories: low, medium, and high. This categorization aids in detecting whether individuals are experiencing mental health issues. By analyzing patterns and trends in the data, researchers can identify potential indicators of mental illness. Data mining techniques are employed to assess the health conditions of different groups, including healthy individuals and those with mental illness. Through data analysis, researchers can uncover correlations and associations between various factors and mental health outcomes.

Balajee Maram
SR University

Read the Original

This page is a summary of: New Analytic Framework of Public Mental Health Prediction Using Data Science, March 2022, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/icstsn53084.2022.9761324.
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