Cameron Hill seemed destined to be a neurologist. His grandmother, Kathleen Principe was a pioneer in electroencephalogram (EEG) technology, inventing the first single patient use EEG headpiece. She founded her own medical supply company to build and sell her inventions and Hill’s mother and uncle joined her in the neurodiagnostic field.
Research has so many transferable skills. It teaches you to be organized, to think down the road and to be able to anticipate and plan for potential roadblocks and how to work with a team.
Cameron Hill
“I always said I’m not going to become a neurologist by default, just because my family loves the brain, said Hill, a fourth-year medical student. “But, throughout my time in medical school, it just became true that I love the brain as well.”
Hill inherited his grandmother’s intellectual curiosity, which led him to research in the social sciences as a BU undergrad and an MPH in healthcare management at BU’s School of Public Health. Hill is completing a long-term research project on the use of artificial intelligence (AI) to analyze eye movement to predict outcomes in comatose patients.
Statistics show that termination of life support is responsible for 80% of deaths in cardiac arrest coma patients. Making the determination of who will or won’t survive a coma is somewhat subjective and the need for more precise diagnostic tools is obvious when it’s estimated that one in six of these patients could have recovered to the point of ambulation and discharge from the hospital.
Observing eye movements is believed to be one predictor of outcomes, but it’s tedious time-consuming work to physically monitor a patient. Hill works in the lab of Charlene Ong, MD, MPHS, which leverages artificial intelligence to improve neuroprognostication in post-cardiac arrest patents in the intensive care unit. In collaboration with a team of computer scientists, the lab developed a machine learning algorithm that automatically detects eye movements in post-cardiac arrest patients. Hill led the process of gathering hundreds of hours of training data from electrodes placed around patients’ eyes and entering it into a computer model to teach it how to interpret patterns of eye movement.
Hill was the lead author of the project’s paper, “Eye movement detection using electrooculography and machine learning in cardiac arrest patients,” which included over 20 co-authors across multiple institutions, published in the online journal Resuscitation in March of 2025 and received a spotlight editorial from the journal’s editor.
“Research has so many transferable skills. It teaches you to be organized, to think down the road and to be able to anticipate and plan for potential roadblocks and how to work with a team,” Hill said.