Open AccessPredictive Research for Mental Health Disease
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i1038.0789s219
Subject(s) - mental illness , identification (biology) , mental health , everyday life , state (computer science) , mental state , disease , data collection , the internet , data science , psychology , random forest , computer science , internet privacy , psychiatry , applied psychology , medicine , artificial intelligence , world wide web , botany , algorithm , pathology , political science , law , biology , statistics , mathematics
Many people are suffering from some kind of mental illness and this number is increasing day by day. Despite major revolutions in medical science exact identification of factor that leading to mental illness is still unknown to the world. Due to its ambiguous nature, mental state of person is a major focus on research these days. With the emergence of smart phones, PCs, internet of things. The amount of data human kind produce everyday is huge and only accelerating. These data are stored in a semi structured way and used to get meaningful relationships and trends in data. Data mining techniques can be efficiently used on this data to find hidden patterns between different attributes of data. This paper describes the prototype to use data mining technique namely Random forests classification to determine person’s mental state based on attributes such as age, gender, life style, education, Occupation, personal income, vision, sleep, mobility, hypertension, diabetes. The system will predict whether a patient is suffering from mental illness or not.