OSLER inHealth provides an R-based environment consisting of software tools that support the generation, management, analysis, and visualization of complex health data to facilitate health-related decision-making. OSLER inHealth was conceived by a team of researchers at Johns Hopkins University and Harvard University affiliated with the Johns Hopkins Individualized Health Initiative (Hopkins inHealth), an initiative dedicated to creating and disseminating statistical tools that harness scientific knowledge to individualize health care. 

The ultimate goal of OSLER inHealth is to improve health decision-making by enabling the identification and tailored treatment of subsets of patients with similar health states and trajectories. Software development is motivated by three research projects that use Bayesian hierarchical models to predict the severity of prostate cancer, the etiology of childhood pneumonia, and the trajectory of clinical depression patients. More information on these case studies can be found here

Software Development Team

Scott Zeger

Director of Hopkins inHealth and Professor of Biostatistics at Johns Hopkins University

Dr. Zeger is an expert in statistical models for longitudinal data.

Vincent Carey

Associate Professor of Medicine at Harvard Medical School

Dr. Carey is an international leader in statistical computations and software design for biomedical applications.

R. Yates Coley

Postdoctoral Fellow in Biostatistics at Johns Hopkins University

Dr. Coley is an expert in Bayesian hierarchical models for estimating patient risk.

Zhenke Wu

Postdoctoral Fellow in Biostatistics at Johns Hopkins University

Dr. Wu is an expert in computational methods for latent variable models.

Julia Bindman

Undergraduate Student at Johns Hopkins University

Ms. Bindman is a pre-med student majoring in Computer Science and Biology.

Questions? Visit our contact page.