Create
Design Project Gallery
Early Prediction of Length of Stay in Hospitalized Patients with Stroke and Traumatic Brain Injury
Team: Team Dolphin
- Program: Biomedical Engineering
- Course: Precision Care Medicine
- Year: 2022
Project Description:
Stroke is one of the leading causes of morbidity and mortality worldwide, and traumatic brain injury (TBI) is one of the major causes of disability in children and young adults. ICU length of stay (LoS) is considered a primary driver of inpatient costs. The prediction of length of stay in the early phase of hospitalization can inform resource allocation and improve clinical decision-making to ultimately reduce medical spending. The team used patient data available in the first 24 hours of stay to predict length of stay for patients with traumatic brain injury and stroke in the NCCU. The predictive features driving length of stay were also identified and ranked.
Project Photo:
A logo of a clock next to a brain, as we are predicting length of stay (time in hospital) for patients afflicted with neurological injuries.
Student Team Members
- Heramb Gupta
- Darsh Patel
- Steven Solar
- Shreya Hariharakumar
- Nihao Sun
- Runtian (Trent) Tang
- Robert D. Stevens
- Casey Overby Taylor
- Joseph L Greenstein
Project Video
Johns Hopkins Design Day 2022 — Early Prediction of Length of Stay in Hospitalized Patients with Stroke and Traumatic Brain Injury