Editorial. Artificial neural networks for neurosurgical diagnosis, prognosis, and management

eurosurgeoNs are faced with a dizzying array of data that need to be analyzed when making clinical decisions about diagnosis, prognosis, and management. Over the last 30 years we have seen the rapid growth in computer processing power and ever-accelerating interest in how to use this computational ability for better data analysis. One aspect of this is whether or not artificial intelligence methods, such as machine learning algorithms and artificial neural networks (ANNs), could improve our capabilities for accurate diagnosis and prognosis and improved patient management. The appeal of ANNs is obvious. They employ diverse types of medical data as inputs and integrate them into categorized outputs. This is, in essence, what clinicians do so the process has some face validity.