“Improving human health by prime insights from data.”
In the last decade, there has been major advances in the production and collection of data, from medical research to patient wellness regimes. These vast new troves of data from electronic health records, claims/billing data, product/disease registries, genetic/genomic databases, medical devices and wearables offer a unique opportunity to make health care more proactive. Transforming these data into insights requires deep understanding of the provenance of the data, the collection procedure of the samples, the intercorrelations among the variables, the quality of the data, and the uncertainty associated with the analytical results from models.
Our overriding objective is to develop, apply and disseminate new methods and software for evidence generation using clinical trial and real-world data, and to bridge the gap from data to insights, and from insights to actionable health care.
For examples of our innovative research projects, please visit our xmeta-project as a comprehensive tool for advanced meta-analysis, and pda-project as an innovative solution for next generation data sharing for multi-institutional studies.
On behalf of our lab members, I want to thank the continuous funding supports from NIH, PCORI and AHRQ.
Dr. Yong Chen shared insights on AI-powered rare disease diagnostics at the International Genomic Medicine Symposium. (Nov 2025)
Dr. Yong Chen is named an MPI on a new $27.2 million NIH initiative to unify Alzheimer’s research data across 10 leading institutions. (Oct 2025) https://ldi.upenn.edu/our-work/research-updates/27-2-million-national-effort-launches-to-unify-alzheimers-research-data/
Check out features on our recent Long COVID studies! Penn Medicine News TIME Magazine The Lancet Infectious Diseases The New York Times The Microbiologist
Dr. Yong Chen’s $8 million grant from the National Institute of Mental Health to develop an AI-driven framework that could transform how we detect and diagnose mental health conditions was