The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …

Stroke is a leading cause of disability and mortality worldwide, necessitating the
development of advanced technologies to improve its diagnosis, treatment, and patient …

Machine Learning (ML) through pattern recognition algorithms is currently becoming an
essential aid for the diagnosis, treatment, and prediction of complications and patient …

Artificial intelligence (AI) is a fast-growing research area in computer science that aims to
mimic cognitive processes through a number of techniques. Supervised machine learning, a …

Stroke ranks among the leading causes for morbidity and mortality worldwide. New and
continuously improving treatment options such as thrombolysis and thrombectomy have …

Background and Purpose—The prediction of long-term outcomes in ischemic stroke patients
may be useful in treatment decisions. Machine learning techniques are being increasingly …

Abstract Machine Learning (ML) delivers an accurate and quick prediction outcome and it
has become a powerful tool in health settings, offering personalized clinical care for stroke …

Ischemic stroke is a cerebrovascular disease with a high morbidity and mortality rate, which
poses a serious challenge to human health and life. Meanwhile, the management of …

Introduction Being able to predict functional outcomes after a stroke is highly desirable for
clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to …

Artificial intelligence technology is a rapidly expanding field with many applications in acute
stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute …