Diagnostic Accuracy of Machine and Deep Learning Methods in Intracranial Hemorrhage Detection: A Systematic Review and Meta-Analysis

Background/Objectives: In this systematic review we investigated the diagnostic accuracy of machine and deep learning algorithms for the detection of intracranial hemorrhage (ICH) and its subtypes such as subarachnoid, intraventricular, intraparenchymal, subdural and epidural hemorrhage. In addition, we investigated their generalizability by comparing methods tested on private vs. public datasets, and FDA- vs. non-FDA-approved algorithms.