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Spotlight on Julianne Murphy


Julianne Murphy successfully defended her dissertation in December 2023 and now holds a PhD in Health and Biomedical Informatics from the Feinberg School of Medicine. Her advisor was Justin Starren, MD, PhD, FACMI, Director of I.AIM's Center for Biomedical Informatics & Data Science.


"Health outcomes after stroke: determinants, complications, and prediction"
My dissertation used machine learning methods to examine bias related to social determinants of health in the prediction of discharge modified Rankin Scale; determine clinical phenotypes of intracerebral hemorrhage at admission; and define complex patient outcomes across multiple domains of health-related quality of life for survivors of subarachnoid hemorrhage. Additional research is needed to validate our predictive models and data-driven cluster findings in other settings, with the ultimate goal of informing targeted interventions that anticipate patient needs and customize post-stroke care.

Julianne received her BA and MS degrees in Biochemistry and Molecular Biology from Clark University. During this time, she worked and studied in Luxembourg and the Netherlands. Her research examined the distribution of microRNA gene copy number across human populations. Prior to joining the Northwestern Medicine Health Sciences Integrated Program (HSIP), she analyzed self-reported risky health behaviors in middle and high-school students at the Worcester Division of Public Health. Her prior experiences include environmental health work at the Association of Public Health Laboratories and corporate medical management at AmeriHealth Caritas. Her research interests include integrating genomic data into EHRs and telehealth initiatives for quality of care improvement. She is a recipient of the NU Data Science Fellowship.

Borders A, Lee King P, Weiss D, Murphy J. 160: improving outcomes for mothers affected by opioids through statewide quality improvement. Am J Obstet Gynecol. 2020; 222:S116

Borders A, Lee King P, Weiss D, Murphy J. 792: Optimizing care for mothers and newborns affected by opioids by understanding disparities in treatment. Am J Obstet Gynecol. 2020; 222:S501-S502