“Utilizing Big Data for Drug Discovery (Repurposing) to Improve Patient and Disease Outcomes” Seminar, Dr. Scott Sutton, UofSC Abstract: Drug repurposing holds the potential to bring existing medications with known safety profiles to new patient populations to accelerate drug development and lower treatment costs. Numerous examples exist for the identification of new indications for existing […]

“Integrating Multi-Modal Biobehavioral Data to Treat Substance Use Disorders” Seminar, Dr. Brett Froeliger, Medical University of South Carolina Abstract: The role of neural circuitry in motivation, reward and drug use will be discussed; along with associations between inhibitory control and relapse vulnerability. These topics will be discussed in the context of ongoing research on the […]

“Leveraging Social Media Technology to Improve Health and Emotional Well-being” Abstract: Dr. Cavazos will present on systematic ways to explore social media posts about mental illness and substance misuse behaviors. Her research has implications for the delivery of online, accessible, and timely social media outreach that could facilitate new and more rapid responses in mental […]

UofSC National Big Data Health Science Conference, Case Competition 2020 The Big Data Health Science Case Competition will be held between February 7th-9th 2020 before the University of South Carolina’s National Big Data Health Science Conference. The Big Data Case Competition is intended to provide enthusiastic teams of graduate and senior undergraduate students with the […]

UofSC National Big Data Health Science Conference The University of South Carolina’s National Big Data Health Science Conference is a signature annual event of the UofSC Big Data Health Science Center (BDHSC). The theme for the 2020 Conference: Unlocking the Power of Big Data in Health – Partnerships among Industry, Government, and Academia. https://www.sc-bdhs-conference.org/ Register […]

Abstract: Group testing involves pooling individual specimens (e.g., blood, urine, swabs, etc.) and testing the pools for the presence of a disease. When individual covariate information is available (e.g., age, gender, number of sexual partners, etc.), a common goal is to relate an individual's true disease status to the covariates in a regression model. Estimating […]