"My whole team in fact are from all walks of life...but the mission and their talent is what matters."

SCRABBLE leverages bulk data as a constraint and reduces unwanted bias towards expressed genes during imputation.

Validating the expected behavior of a customized CDS system in the high-volume, complex environment of the live EHR is a challenging problem.

"Ultimately, researchers would leverage knowledge from single-cell data into a deeper understanding of organ development and function, to better inform precision treatments to advance children’s health,” Deanne Taylor, PhD, DBHi Director of Bioinformatics "

Using gene expression data to predict the outcome of a patient's tumor makes biomarker discovery a compelling tool for improving patient care.

"We want to enable science to unfold as easily and effortlessly as possible, yet at the same time, be good stewards of patients’ data."

Gain key insights about health IT safety in this podcast.

Automated programs can identify which sick infants in a neonatal intensive care unit (NICU) have sepsis hours before clinicians recognize the life-threatening condition. A team of data researchers and physician-scientists tested machine-learning models in a NICU population, drawing only on routinely collected data available in electronic health records (EHRs).

With high-throughput sequencing methods continuously yielding floods of new information, how can clinicians keep up with updated data for patients who have already received genetic test results?

Arcus will link the vast quantities of pediatric data CHOP generates as a clinical enterprise with the data it generates as a research enterprise to produce a more holistic picture of pediatric health and disease.