Artificial intelligence applied in acute ischemic stroke: from child to elderly

This review will summarize artificial intelligence developments in acute ischemic stroke in recent years and forecasts for the future. Stroke is a major healthcare concern due to its effects on the patient's quality of life and its dependence on the timing of the identification as well as the treatment. In recent years, attention increased on the use of artificial intelligence (AI) systems to help categorize, prognosis, and to channel these patients toward the right therapeutic procedure. Machine learning (ML) and in particular deep learning (DL) systems using convoluted neural networks (CNN) are becoming increasingly popular. Various studies over the years evaluated the use of these methods of analysis and prediction in the assessment of stroke patients, and at the same time, several applications and software have been developed to support the neuroradiologists and the stroke team to improve patient outcomes.

Automated summary

This review summarizes the recent developments and future forecasts of artificial intelligence in acute ischemic stroke. The use of artificial intelligence systems, particularly machine learning and deep learning using convoluted neural networks, has gained attention in categorizing, predicting, and guiding the right therapeutic procedures for stroke patients. Various studies and software applications have been developed to assist neuroradiologists and stroke teams in improving patient outcomes.