1、MACHINE-LEARNED IDENTIFICATION OF PRESCRIPTION OPIOID MISUSE AND ITS PSYCHOSOCIAL AND BIOMEDICAL DETERMINANTS IN PEOPLE LIVING WITH HIV Cheuk Chi(George)Tam,Ph.D.,M.S.,M.A.Research Assistant ProfessorDepartment of Health Promotion,Education,and BehaviorArnold School of Public HealthResearch faculty
2、member in Health Promotion,Education,and Behavior at Arnold School of Public Health,USCApply advanced methodologies to examine or address psychosocial aspects of POM or relevant treatment Cascade of care for opioid use disorderTechnology-based intervention for prescription opioid misuse Clinical tra
3、ining in psychotherapy and HIV prevention interventionDoctoral training in Health Psychology focusing on psychometric and theory-driven investigation of prescription opioid misuse(POM)among vulnerable populationBackgroundResearch PlanThe successful risk assessment and POM prevention in PLWH relies o
4、n valid measures of POM and the understanding of multifaced features of POM,the use of multiple sources of high-dimensional data to examine the complex mechanism underlying the interactions among biomedical,psychiatric,and social determinantsAI modeling on aggregated data from various sources of cli
5、nical and addiction-related datasets(EHRs,lab reports,prescription records,self-reported surveillance,and state-based data)Frontier insights and models of complex medical and psychiatric needs of people with POM/treatmentValid use of HIV surveillance EHR dataTraining AimsGapsMy previous training rel
6、ied solely on self-collected psychometric data from a selected group of the target populationMy data analytic skill sets are built upon traditional statistics,which has various restrictions on data(e.g.,normality,linearity,outliers,and non-collinearity),R25 Fellowship Mentored TrainingBankole Olatos