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

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 …

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with
acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate …

Brain imaging is essential to the clinical care of patients with stroke, a leading cause of
disability and death worldwide. Whereas advanced neuroimaging techniques offer …

Background and purpose Acute stroke caused by large vessel occlusions (LVOs) requires
emergent detection and treatment by endovascular thrombectomy. However, radiologic LVO …

The identification and treatment of patients with stroke is becoming increasingly complex as
more treatment options become available and new relationships between disease features …

Stroke is an emergency in which delays in treatment can lead to significant loss of
neurological function and be fatal. Technologies that increase the speed and accuracy of …

Artificial intelligence (AI) is having a disruptive and transformative effect on clinical medicine.
Prompt clinical diagnosis and imaging are critical for minimizing the morbidity and mortality …

Stroke is a leading cause of long-term disability, and outcome is directly related to timely
intervention. Not all patients benefit from rapid intervention, however. Thus a significant …

Background In recent years, machine learning (ML) has had notable success in providing
automated analyses of neuroimaging studies, and its role is likely to increase in the future …