Park Lab | Program for Hospital and Intensive Care Informatics

Our mission is to derive actionable information from healthcare data to improve efficiency and quality of care in hospitalized or critically ill patients. Using monitoring devices and digitized patient data, we implement statistical and machine learning decision support tools to detect physiologic state changes and identify opportunities for early intervention to change outcome.

Ongoing projects include:

• Detecting delayed cerebral ischemia in subarachnoid hemorrhage patients
• Goal-directed perfusion in subarachnoid hemorrhage patients leveraging autoregulation indices and adjunctive neuromonitoring
• Intracranial pressure waveform analysis to detect ventriculitis
• Automated time-varying measures to predict shunt dependency in acute hydrocephalus
• Deriving endotypes of hospitalized COVID patients that predict outcome
• Noninvasive monitoring to risk-stratify chronic subdural hemorrhage patients
• Neuromonitoring to optimize post-operative care of pediatric single ventricle heart surgery patients
• Noninvasive estimation of intracranial pressure

Publications

• Complete bibliography is listed on the National Library of Medicine website.
• Please click here to download a list of selected publications as a PDF file.