In Neurosurgery clinics of North America
Big data studies are on the rise in vascular neurosurgery. Advanced computer processing power combined with vast amounts of digitized data collected and stored by electronic medical records have led to studies using machine learning, deep learning algorithms, and their applications-artificial intelligence. Big data is challenging the gold standard model of randomized controlled trials introducing more pragmatic research designs including registries and registry-based randomized trails. There is a maturation of cerebrovascular disease studies. Studies have larger patient sample sizes allowing for more compelling conclusions that we reach with higher confidence. This pertains to diagnosis, treatment, outcomes, and a more nuanced understanding of less common presentations of illnesses. The following review will critically discuss big data applications in vascular neurosurgery as well as its implications in quality improvement, innovation, and global neurosurgery.
Ghannam Moleca M, Davies Jason M
Artificial intelligence, Big data, Carotid stenosis, Intracranial aneurysm, Machine learning, Moyamoya, Registry, Vascular neurosurgery