The Promise and Challenges of Artificial Intelligence to Transform TBI Management
AI Could Advance Diagnostic Speed, Improve Prognosis, and Enable Personalized Rehabilitation Programs
Traumatic brain injury (TBI) is a leading cause of disability and death worldwide, impacting 50 to 60 million people each year. A new study by students and faculty at New York Medical College, published in Life, emphasizes how artificial intelligence (AI) is quickly transforming TBI management with the potential to do even more in the future.
“As healthcare technology advances, AI has emerged as a promising tool in enhancing TBI rehabilitation results,” says Seun Orenuga, SOM Class of 2027, lead author on the study. “The integration of AI into TBI management can advance diagnostic speed and accuracy, especially in acute settings, by rapidly analyzing imaging and other clinical data, improve prognosis by aiding clinicians in making more informed decisions about treatment and resource allocation, and enable personalized, adaptive rehabilitation programs based on patient progress and predicted outcomes.”
According to the study, AI-driven algorithms are being developed to be highly effective in forecasting functional outcomes and personalizing rehabilitation plans based on patient data. Imaging analysis can also be pre-screened for abnormalities to simplify work for human radiologists and expedite diagnosis and treatment decisions.
“The degree of accuracy reported in these models is surprisingly good and shows the potential for AI to impact decision-making in TBI management,” says Orenuga. “It’s also interesting that the main barriers to clinical adoption are not so much technical, but ideological, related to algorithmic bias and ethical considerations.”
According to Orenuga, an important question still to consider is how well AI models perform in real-world, diverse clinical settings, as most current models are trained on data from high-income countries, raising concerns about generalizability to other populations.
“Looking ahead to the future, it is not just about treatment—it is about transformation and making healthcare more accessible, efficient, and patient-centered,” says Orenuga. “Clinicians should approach AI and AI-driven tools as supplements and not replacements for clinical judgment. AI can enhance, but not substitute, the balanced reasoning and patient-centered care that comes from the working experience and personable nature of clinicians.”
