WSEAS Transactions on Biology and Biomedicine
Print ISSN: 1109-9518, E-ISSN: 2224-2902
Volume 16, 2019
Proposal of hybrid data mining method for early detection of depression
Authors: , ,
Abstract: In Japan, neuropsychiatric disorders are estimated to contribute to 24.6% of the global burden of disease. The government launched a suicide/depression countermeasure project team, conducted interviews and discussions with experts, analyzed data on suicide such as demographic statistics, and actively examined measures based on the actual situation of suicide. As we can see from these current situations, we think that the problem of suicide in the current situation in Japan is an issue that must be actively addressed and aimed at improvement. In this paper, we focus on depression which is counted as the most common cause and motive among suicides. There are many people who have not had a medical examination even if they are suffering from depression, and they tend to be aggravated when they see a problem and have a consultation with a specialist. We consider early detection of disease as an issue.
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Keywords: Hybrid data mining, Wearable sensors, Detection of depression, Neuropsychiatric disorders, QIDS-J, LOC, SRS-18
Pages: 114-120
WSEAS Transactions on Biology and Biomedicine, ISSN / E-ISSN: 1109-9518 / 2224-2902, Volume 16, 2019, Art. #14