NIRVATECHS: Psychological analyzer and Personalities types classifier

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dc.contributor.advisorDmaidi, Mona
dc.contributor.authorKhanfer, Ghaith
dc.contributor.authorSawafta, Walaa
dc.date.accessioned2020-03-13T10:55:21Z
dc.date.available2020-03-13T10:55:21Z
dc.date.issued2018
dc.description.abstractMental disorders lead to difficulties in professional, educational, social and marital relationships. The aim of this study is to assess the prevalence and nature of the mental. Failure to detect mental disorder deprives patients of effective treatment. Therefore, the most important goal of our projects is to analyze the symptoms of individuals and apply every change to the situation to detect people with depression. Innovative and economic strategies for collecting and interpreting data for the prevention of depression are critical tools in preventing depression. Computational methods such as natural language processing (NLP) are combined with automated learning techniques (ML) that use current data from social media and mobile phone. Natural Language Processing Techniques (NLP) can be used to draw conclusions about people's mental states from what they write on Facebook, Twitter, and other social media. These inferences can then be used to create online paths to direct people to health information. So, our research is about how to build a mobile AI application that specializes in mental and behavioral health care and provides many smart services and features to help users improve their mental health, help them make decisions in daily activities with recommendations, and improve their lives through many other exciting features Interesting and proposed new prototype.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11888/14924
dc.language.isoenen_US
dc.titleNIRVATECHS: Psychological analyzer and Personalities types classifieren_US
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