The development team supporting our UCSF Information Commons Environment has been busy building and improving data assets, analysis tools, compute environments, and, of course, providing support and data science connections […]
Sara Murray, MD
Using EHR data for quality and value improvements
Dr. Murray is leading the Advanced Analytics & Innovation team, she is involved in large analytic projects using EHR data to inform quality and value improvement efforts at the medical center. She is interested in predictive analytics and has done research in EHR phenotyping.
Stephan Sanders, PhD
Using genomics and bioinformatics to understand the etiology of developmental disorders
Sanders Lab aims to identify the etiology of developmental disorders through the discovery of genetic risk factors. They aim to continue progress, leverage findings to build a complete understanding of ASD, & extend this approach to other human disorders, including congenital malformations.
Julian Hong, MD, MS
Developing and implementing computational tools in oncology to improve patient care
Dr. Hong’s research program focuses on combining clinical domain knowledge with data science to generate insights from real world data, develop actionable computational tools, and evaluate the benefit of these advances in personalized cancer care.
Jingjing Li, PhD
From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases
The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. The ultimate goal is to build data-driven frameworks to detect diseases before symptoms emerge and to achieve precision health management.
Majumdar will run the Center for Intelligent Imaging’s operations to accelerate the application of artificial intelligence (AI) technology to radiology.Read Article
Study suggests tau tangles, not amyloid plaques, drive daytime napping that precedes dementia.Read Article
BCHSI faculty Marina Sirota led the first cohort of the AI4All program, focused on promoting greater diversity and inclusion in the field of AI in biomedicine.Read Article
Geoff Tison, MD, MPH
Applying machine learning and deep-learning techniques to large-scale electronic health data
Dr. Tison applies machine learning and deep-learning techniques to large-scale electronic health data from heterogeneous sources in order to achieve the goal of personalized cardiovascular prognosis and disease prevention.
Benjamin Rosner, MD, PhD
Understand use of CLIIR to improve quality and value of healthcare
Audit-log data captures moment to moment clinical care processes within EHR. It makes these labor-intensive approaches obsolete, providing more comprehensive data faster with more accuracy. Taking this audit-log data and combining it with clinical data enables us to research the impact of provider workflows, behaviors and interactions with the EHR on patient outcomes.
Romain Pirrachio, MD, PhD
Applied biostatistical research, machine Learning and predictive analytics in critical care
Dr. Pirracchio focuses on three clinical research areas including evaluation and optimization of daily cares in the intensive care unit. He is also broadly interested in problems of causal inference and prediction, particularly developing novel methodologies for addressing scientific questions using complex observational data subject to sampling biases.
BCHSI’s Director has been inducted into the College of Fellows of the AIMBE in recognition of his contributions to creating a precision medicine roadmap with open access dataRead Article
Julia Adler-Milstein, PhD
Examining the use of IT in healthcare delivery
Dr. Adler-Milstein’s research assesses the progress of health IT adoption; the impact of such adoption on healthcare costs and quality; and the relationships between market, organizational, and team structure and health IT use. A core focus of her work is on health information exchange and interoperability.