Research Diabetes Data analysis
Epidemiologist and researcher Randi K. Johnson, PhD, MPH, assistant professor of biomedical informatics at the University of Colorado School of Medicine, is diving into how maternal pregnancy factors impact the offspring’s risk of developing type 1 diabetes (T1D) with the assistance of a $500,000 grant from JDRF Australia. The grant is supported by funding from The Leona M. and Harry B. Helmsley Charitable Trust to JDRF Australia.
A newly-released consensus report authored by more than 200 academic experts from around the world, including three health researchers from the University of Colorado School of Medicine, points to exciting opportunities in precision medicine in diabetes prevention and care.
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
