Data science in public mental health : a new analytic framework

Silva, HCE, Saraee, M and Saraee, MH ORCID: 2019, Data science in public mental health : a new analytic framework , in: IEEE Symposium on Computers and Communications June 30 - July 3, 2019 – Barcelona, Spain.

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Understanding public mental health issues and finding solutions can be complex and requires advanced techniques, compared to conventional data analysis projects. It is important to have a comprehensive project management process to ensure that project associates are competent and have enough knowledge to implement the process. Therefore, this paper presents a new framework that mental health professionals can use to solve challenges they face. Although a large number of research papers have been published on public mental health, few have addressed the use of data science in public mental health. Recently, Data Science has changed the way we manage, analyze and leverage data in healthcare industry. Data science projects differ from conventional data analysis, primarily because of the scientific approach used during data science projects. One of the motives for introducing a new framework is to motivate healthcare professionals to use "Data Science" to address the challenges of mental health. Having a good data analysis framework and clear guidelines for a comprehensive analysis is always a plus point. It also helps to predict the time and resources needed in the early in the process to get a clear idea of the problem to be solved.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Depositing User: Prof. Mo Saraee
Date Deposited: 02 Jul 2019 10:37
Last Modified: 16 Feb 2022 02:17

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