Human health is influenced by an extraordinarily complicated range of factors, from genetics and socioeconomics to air quality and lifestyle factors like exercise. Princeton Precision Health(Link is external) (PPH) is taking aim at this whole complex picture, bringing together a unique combination of experts, giant datasets and advanced computational methods to gain a comprehensive understanding of how to make and keep humans healthy.
The initiative’s 10 core faculty members include experts in sociology, psychology, computer science, engineering, genomics, environmental science, epidemiology and medicine, and PPH has awarded 22 endowment-funded seed grants to enable researchers from across the University to investigate health-related topics, such as the impact of technology on mental health and how computer vision tools can help diagnose autism.
Whereas faculty within a given academic department apply similar methods to different problems, “PPH aims to apply widely different methods and approaches to a common grand challenge,” said Matthew Salganik, a professor of sociology and core PPH faculty member. The grand challenge: to achieve a deep understanding of human health — at the molecular, individual and societal level — using sophisticated computational methods that integrate all factors of health to reliably predict outcomes for individuals and groups. To read the full story.