When Shane Ridoux and Emily Aaron graduated from college with math degrees, neither had genomics as a future career option on their radar. Now, after two months into a new graduate degree program partnership between the University of Colorado Department of Biomedical Informatics (DBMI) and the CU Denver Department of Mathematical and Statistical Sciences, the two say they’re excited about joining the burgeoning field.
Exploring diverse ancestry is a critical factor in furthering medical research.
A new study published in Nature Genetics from researchers in the Department of Biomedical Informatics (DBMI) at the University of Colorado School of Medicine, in partnership with the University of California San Francisco and Stanford University, is the largest of its kind that focuses on ancestry correlations with biomedical traits and the first study to examine the role of genetic variants across diverse ancestries in regulating gene expression.
Community Faculty Diversity Health equity Social Justice
Janani Ravi, PhD, assistant professor in the Department of Biomedical Informatics at the University of Colorado School of Medicine, didn’t intend to challenge the status quo when she began her career in data science. But after several years of working diligently on her research in computational biology as a graduate student at Virginia Tech, as a postdoc at Rutgers Biomedical and Health Sciences, and then as an independent researcher/faculty member at Michigan State University (MSU), she began to see a pattern emerge, particularly on the conference circuit.
IEEE Xplore
July 10, 2024
In this manuscript we explore a computationally efficient approximation to hard data consistency. We present results when adding this data consistency layer into two existing networks designed for MRI reconstruction. After retraining with the additional consistency layer, the networks show improved out-of-distribution performance and suppression of hallucinations.
JAMIA
July 10, 2024
The publication of the Phoenix criteria for pediatric sepsis and septic shock initiates a new era in clinical care and research of pediatric sepsis. The phoenix R package and Python module enable researchers to apply the Phoenix criteria to electronic health records (EHR) datasets and derive the relevant indicators, total scores, and sub-scores.
JAMIA
July 10, 2024
The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven’s Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline.
SPIE
July 03, 2024
Nick Dwork, PhD, and co-authors present a method that combines compressed sensing with parallel imaging that takes advantage of the structure of the sparsifying transformation.
Kara Mason
