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Accurately identify the patients who will benefit from treatment in a neurocritical care environment and those that will do equally well in a less resource-intense environment.

The overarching goal is to optimize medical and triage decision-making for hospitalized neurologic and neurosurgical patients in order to align resources with clinical needs. This will be accomplished via prognostic and predictive enrichment strategies that leverage multidimensional data and artificial intelligence.


Predict complications in the post-operative neurosurgical period, and neurological deterioration for all neurocritical care unit (NCCU) patients so clinicians can make accurate, optimized, and personalized decisions regarding neurosurgical and NCCU patients. 


Neurocritical Care Research

Questions we're asking that inform us on how to best care for patients include:


Can we develop and validate a highly accurate, personalized NCCU triage score for post-operative neurosurgical complications?

Risk Prediction

Can we develop and validate a personalized risk prediction index of neurological deterioration for patients admitted to the NCCU?

Decision Support

How do we determine the safety, feasibility, efficacy, and cost effectiveness of decision support systems developed using predictive analytics from aims 1 and 2?

Clinical Trials

Every patient benefits from our innovative thinking on the management of severe neurologic conditions, informed by our clinical experience as well as new insights from the front lines of research.


Patient Care for Neurocritical Care 

Patients in Johns Hopkins NCCUs benefit from a seasoned multidisciplinary group of neurologists, anesthesiologists, neurosurgeons, nurse practitioners and critical care nurses. Find out more about neurocritical care.


Center Directors

Scientific Leads

Data Managers

Data Scientist

Han Kim, B.S.E., M.S.E.

Research Group

Laboratory of Computational Intensive Care Medicine

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