A Decision Support System for the Prediction of Drug Predisposition Through Personality Traits.

The topic of recreational drug consumption is still largely controversial around the globe. Factors that predispose people and lead to initial drug use include, among others, personality traits. The study of personality is a well-established domain of psychology, with multiple models having been developed, which are capable of predicting predisposition to a certain degree. Furthermore, addiction and other mental health issues carry stigma, which inhibits affected people from reaching out for support. Online web-based tools and automated systems have shown to be fairly effective in tackling stigma by eliminating the human factor. As such, a web-based decision support system (DSS) is developed and made publicly available, in order to inform users about their drug predisposition through an online personality survey. To accomplish the latter, the DSS utilizes multiple machine learning algorithms to extract patterns of personality, as modeled by the Big Five personality traits. The utilized algorithms turn out to be effective at predicting drug use for most of the 17 drugs that are considered, even in cases of high-class imbalance.

Mobile Application for Monitoring and Preventing Cognitive Decline Through Lifestyle Intervention.

Diagnosing and preventing Alzheimer's disease is a complex task, partly due to being characterized by a lengthy asymptomatic stage. In order to tackle this, most preclinical studies are multidimensional in nature and largely focus on prevention through lifestyle interventions, such as improving nutrition and introducing physical as well as cognitive exercise. With the widespread use of mobile smart devices today, mobile health applications can help inform high-risk individuals at a low cost, while also aiding in the prevention of cognitive decline through constant virtual coaching services that contribute to lifestyle interventions. Under this light, a mobile application is developed in the context of this paper that provides risk assessment of individuals, daily monitoring of factors that have been found to help prevent cognitive impairment, and individually tailored guidance based on the individual's progress. The developed application is also capable of reassessing users' risk to track their progress, while also providing these services in an intuitive and user-friendly manner, which could enable the future development of more accurate models through the collected data.