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      Applying Data Science to Behavioral Analysis of Online Gambling

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      Current Addiction Reports
      Springer Science and Business Media LLC

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          Machine Learning Approaches for Clinical Psychology and Psychiatry

          Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.
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            Cross-trial prediction of treatment outcome in depression: a machine learning approach.

            Antidepressant treatment efficacy is low, but might be improved by matching patients to interventions. At present, clinicians have no empirically validated mechanisms to assess whether a patient with depression will respond to a specific antidepressant. We aimed to develop an algorithm to assess whether patients will achieve symptomatic remission from a 12-week course of citalopram.
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              Online Gambling Addiction: the Relationship Between Internet Gambling and Disordered Gambling

              One of the most significant changes to the gambling environment in the past 15 years has been the increased availability of Internet gambling, including mobile; Internet gambling is the fastest growing mode of gambling and is changing the way that gamblers engage with this activity. Due to the high level of accessibility, immersive interface and ease at which money can be spent, concerns have been expressed that Internet gambling may increase rates of disordered gambling. The current paper aimed to provide an overview of the research to date as well as highlight new and interesting findings relevant to Internet gambling addiction. A comprehensive review of the existing literature was conducted to provide an overview of significant trends and developments in research that relates to disordered Internet gambling. This paper presents research to inform a greater understanding of adult participation in Internet gambling, features of this interface that may impact problem severity, the relationship between Internet gambling and related problems, as well as considering the role of the wider spectrum of gambling behaviour and relevant individual factors that moderate this relationship.
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                Author and article information

                Contributors
                Journal
                Current Addiction Reports
                Curr Addict Rep
                Springer Science and Business Media LLC
                2196-2952
                September 2019
                July 15 2019
                September 2019
                : 6
                : 3
                : 159-164
                Article
                10.1007/s40429-019-00269-9
                739d0ff7-85f5-4ecc-be35-d24a2c4ce576
                © 2019

                http://www.springer.com/tdm

                http://www.springer.com/tdm

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