Turkish Neurosurgery
A systematic review on machine learning in neurosurgery: the future of decision making in patient care.
Emrah Celtikci1
1University of Pittsburgh Medical Center, Neurological Surgery, Pittsburgh,
DOI: 10.5137/1019-5149.JTN.20059-17.1

The current practice of neurosurgery depends on clinical practice guidelines and evidence-based research publications that derive results using statistical methods. However, statistical analysis methods have some limitations like; inability to analyze non-linear variables, requiring setting of a level of significance, being impractical for analyzing large amounts of data and possibility of human bias. Machine learning is an emerging method for analyzing massive amounts of complex data which relies on algorithms that allow computers to learn and make accurate predictions. In the past decade, machine learning was increasingly implemented in medical research as well as neurosurgical publications. This systematical review aimed to assemble the current literature on neurosurgical publications that utilized machine learning, and to inform neurosurgeons on this novel method of data analysis.