Why the study?
Stress is an epidemic generating many diseases and suicide, prompting an evaluation of research conducted on stress using emerging techniques such as machine learning.
Machine learning techniques, particularly Support Vector Machines, are effective in classifying stress signals.
May aid stress monitoring tools; leaves open prospective validation before clinical use.
Stress is one type of epidemic of current world. It generates many diseases and is a big source of human suicide. The main aim of this paper is to determine the work of this study conducted on stress using emerging techniques such as machine learning. This study created a comprehensive image for the work of machine learning in stress management. This study completed in some steps including data collection using closest keywords on Web of Science (WoS) database, design network visualization based on previous data, evaluation of selected research article, and finally conclude the all results. We used 4 closest keywords, 5 research articles, 3 publishers, and 4 journals to analyze the work. The results showed that Support Vector Machine (SVM) easily classify the signals. This study mentioned the future direction for the upcoming research in more scientific and significant manner.
No takes yet. Share an insight, caveat, or question.
Akhtar et al. (2020) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: