We are requesting faculty proposals for Precision Care Medicine, a two-semester course offered at the Johns Hopkins Whiting School of Engineering (EN.580.680-681 and EN.580.480-481) in which students are co-mentored by clinical faculty in the SOM and by engineering faculty in the Department of Biomedical Engineering/Institute for Computational Medicine. Course projects are designed to solve focused problems in clinical medicine by leveraging mechanistic hypotheses, well-defined datasets and statistical and machine learning models.
SOM faculty have the opportunity to lead a team of graduate and undergraduate WSE students in accomplishing data-driven projects with a computational focus. Course faculty engage with student teams in weekly one-hour meetings (Zoom or in-person) and are responsible for mentoring students by discussing methods, critically reviewing results and providing clinical context and impact. Prior training in engineering or machine learning is not a requirement for faculty leads.
Now in its fifth year, the course has included groups modeling onset of acute physiological crises like sepsis, seizures, acute kidney injury, or delirium, biomarkers of successful kidney transplantation, neurological significance of eye movement abnormalities, and outcome after cardiac arrest or traumatic brain injury. Several of these projects have been presented at national or international meetings and/or published in peer-reviewed journals.
For example:
- Digital signatures for early traumatic brain injury outcome prediction in the intensive care unit
- SWIFT: A deep learning approach to prediction of hypoxemic events in critically-Ill patients using SpO2 waveform prediction
- Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning
- Computational signatures for post-cardiac arrest trajectory prediction: Importance of early physiological time series
Interested SOM faculty should submit a concise proposal by completing the intake form. All proposals will be reviewed by a BME/SOM advisory committee. Selection criteria include impact of the stated problem/solution, immediate availability of the proposed dataset, and ability of faculty to commit over two semesters. Email your proposal and any questions to Dr. Robert Stevens at [email protected] before the deadline of June 30, 2022.
