Use of artificial intelligence in diagnosis and prognosis of traumatic brain injury: a scoping review

Traumatic Brain Injury (TBI) has been increasingly recognized as a leading cause of death and disability worldwide.ObjectiveTo summarize clinical applications of artificial intelligence, including machine learning and deep learning, in the diagnosis and prognosis of traumatic brain injury.MethodsThe authors conducted a scoping review of original clinical research studies on humans published in English after January 1, 2014. A search was performed using PubMed, including PMC, MEDLINE, and Bookshelf. The search terms were applied to the title field and included: (TBI) AND (Artificial Intelligence OR Machine Learning OR Deep Learning). Studies meeting inclusion criteria were screened and selected for review. The reference lists of the included studies were also screened to identify any additional eligible articles.ResultsOf 493 studies identified, seven met the inclusion criteria and were included in the analysis, which summarizes study title, publication year, study objective, key findings, and conclusions.ConclusionArtificial intelligence shows promise in aiding diagnosis and improving prognostic insights in traumatic brain injury. Although few clinical trials have been conducted, early results are encouraging. Future progress will require more clinical studies and efforts to address the current limitations of AI tools in medicine.