Artificial intelligence applications in acute ischemic stroke

Acute ischemic stroke (AIS) accounts for more than half of stroke cases and results in severe outcomes from physical disabilities, mental disorders to death. Timely treatment could save brain tissue as more as possible. However, the treatment for AIS should take many factors into consideration, such as extent of lesion, time from onset to treatment, collateral circulation, and so on. Given the emergency of the treatment, the radiologists and neurologists are required to make complex decisions with a large data in a limited time. For precise and timely management, Artificial intelligence (AI) have been applied to facilitate diagnosis of AIS, evaluation of key imaging features, selection of candidates for therapeutic intervention, and prediction of short- and long-term functional outcomes. Many studies have provided diverse models for various utilities assisting the diagnosis and treatment of AIS. Many AI applications have been applied in clinical practice to aid clinicians. In this paper, we reviewed the current AI-driven applications in AIS-related assessment to reveal the current situations and the performance of the emerging AI models.