@inproceedings{scholars12625,
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
         journal = {2020 International Conference on Computational Intelligence, ICCI 2020},
           title = {Mobile Application to Predict Future Risk of Depression},
           pages = {45--50},
            note = {cited By 0; Conference of 2020 International Conference on Computational Intelligence, ICCI 2020 ; Conference Date: 8 October 2020 Through 9 October 2020; Conference Code:164916},
            year = {2020},
             doi = {10.1109/ICCI51257.2020.9247686},
        keywords = {Diseases; Forecasting; Intelligent computing; Mobile computing, Developed applications; Mental illness; Mobile applications; Number of peoples; Similar pattern; Web technologies, Application programs},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097558512&doi=10.1109\%2fICCI51257.2020.9247686&partnerID=40&md5=80f4aef019eb0dc76aca13a759f1c579},
        abstract = {Depression has been a major concern and is having some negative results. The number of people who get depressed continues to grow, many of them often fail to communicate with counselors, which inevitably exacerbate one's mental illness. Currently, most of the available applications provide a depression test for a person's current condition, but do not predict future risks. The aim of the paper is to report on a mobile application called "Mental Checker"which provides a platform for people to predict their future risk of depression as well as to obtain insights into related depression information. The mobile application is developed using Ionic, a software using Web technologies such as CSS, HTML5 and Sass. Data on symptoms of depression is to be analyzed to understand similar patterns of people suffering from depression. Prediction will be made based on the obtained patterns. The developed application may help controlling number of people suffering from depression. {\^A}{\copyright} 2020 IEEE.},
          author = {Jabarullah, J. M. and Ahmad, W. F. W.},
            isbn = {9781728154473}
}