Through integrated research, education, and collaboration, Wisc-PRISM works to transform data into knowledge that meaningfully improves outcomes for critically ill children.
Who we are
Wisc-PRISM (Pediatric Critical Care Research in Informatics, Statistics, and Modeling) advances pediatric critical care through data-driven innovation. Our group leverages high-resolution physiologic data, electronic health records, and machine learning to build predictive models, apply causal inference methods, and design scalable informatics solutions that improve outcomes for critically ill children.
What we do
Our research spans predictive analytics, multimodal neuromonitoring, and rigorous statistical modeling, with a central focus on translating insights into real-world clinical practice. By integrating principles of learning health systems and global health informatics, PRISM seeks to reduce health disparities and advance precision medicine in pediatric intensive care settings worldwide.
Anchored in its close relationship with the pediatric intensive care unit and a particular focus on acquired brain injury, our group integrates clinical experience with analytical research to sustain a continuous cycle between bedside practice and scientific discovery. We actively mentor trainees in advanced analytics, clinical informatics, and pediatric neurocritical care. Our team contributes to curriculum development for students, residents, and fellows, fostering interdisciplinary expertise and methodological rigor.
Current projects
- Prediction of clinically-significant cerebral edema in pediatric diabetic ketoacidosis (DKA)
- Detecting heterogeneity of treatment effect in pediatric randomized controlled trials
- Development of a PICU learning health system (LHS) model
- Refinement of causal discovery techniques using large electronic health record datasets
- Description and prediction of neurodevelopmental outcomes with acquired brain injury and congenital heart disease
- Understanding causal factors related to effective treatment of status epilepticus
- Prospective observational trial of transcranial doppler measures of cerebral blood flow in children with critical illness
Join us!
We welcome motivated trainees and collaborators from diverse disciplines, including medicine, biostatistics and medical informatics, data science, engineering, and global health. Opportunities include:
- Conducting research in predictive modeling, causal inference, and ICU data science
- Receiving mentorship in study design, statistical analysis, and machine learning
- Developing collaborative, scalable multi-site data pipelines and global health solutions
Want to learn more? Check out the Department of Pediatrics “How to Join a Research Group” webpage.
Neil Munjal, MD, MS
Assistant Professor
nmunjal@wisc.edu