Synopsis

The use of artificial intelligence and machine learning for stroke research and clinical applications are increasing exponentially every year. Applications in stroke research focus on the extraction of phenotypes that can help in diagnosis, prognosis or management of stroke patients. These applications tend to fall into two major categories – classification or segmentation. We will briefly review some of the more frequently used applications in the domains of acute ischemic stroke and hemorrhage detection. We will also discuss some of the potential pitfalls and ethical questions that may arise.