BCBI research involves use of data, computing, and technology to advance biomedical discovery and healthcare delivery.
BCBI research involves use of data, computing, and technology to advance biomedical discovery and healthcare delivery.
The overarching research goals of BCBI are to develop, deploy, and evaluate computational and data science approaches to best use biomedical and health data for improving patient care. To this end, our research activities are a major application area for programs such as those within Brown’s Data Science Initiative (DSI).
There is significant need for analytic approaches to advance understanding of the molecular underpinnings of disease and enable such insights to be used within clinical contexts. BCBI is developing translational bioinformatics approaches for incorporating deep biological knowledge into clinical practice. These efforts aim to complement synergistic research programs at Brown, including those being led by the Center for Computational Molecular Biology (CCMB).
A range of approaches and resources are needed for enabling the discovery, management, and evaluation of new health knowledge. BCBI is contributing to research involving the transformation of data into actionable knowledge as part of the Advance-CTR Biomedical Informatics, Bioinformatics, and Cyberinfrastructure Enhancement (BIBCE) Core.
Concomitant with the widespread adoption of electronic health record (EHR) systems within the healthcare data ecosystem, there is an opportunity to transform the practice of medicine through effective use of digital data. Within BCBI, the Clinical Informatics Innovation & Implementation (CI3) Laboratory is exploring use of EHR data from clinical partners (e.g., Lifespan, Care New England, and VA Providence Health Care System) for supporting clinical practice as well as research programs.
There is an increasing need to address the diversity of consumer or patient views. BCBI is involved with the development of information structures and approaches for supporting patient-centric health care needs. Through Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP) projects, qualitative and quantitative methods are being used to better understand COVID-19 testing and vaccination for the Hispanic/Latinx populations and for high risk children in Rhode Island.
The emergence of health information exchanges and population level monitoring systems presents an unprecedented opportunity to develop computational approaches for studying healthcare delivery and quantifying the impact of healthcare reform initiatives. In partnership with the Brown University School of Public Health, Rhode Island Quality Institute (RIQI), and Rhode Island Department of Health (RIDOH), informatics approaches are being developed to support research motivated by State needs as part of the Precision & Population Medicine Informatics (P2MI) Lab.
Over the last two decades, global health informatics has emerged as a new discipline supporting the design, development, implementation and evaluation of health information systems (HIS) in a wide range of environments especially in low and middle income settings. The Clinical & Global Health Informatics Evaluation (CGHIE) Lab supports work on the OpenMRS open source EHR cofounded by Dr. Fraser.
A breadth of methods are needed to extract knowledge from structured and unstructured data across the spectrum of biomedicine an health care. The Biomedical Artificial Intelligence (BAI) Lab is actively involved in the development and evaluation of machine learning, information retrieval, and natural language processing techniques.
“ Biomedical Informatics is broadly defined as the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health ”