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

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

Background Randomized trials involving patients with stroke have established that
outcomes are improved with the use of thrombectomy for large-vessel occlusion. These trials …

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining
increasing interest and is being incorporated into many fields, including medicine. Stroke …

Purpose To evaluate the performance of an artificial intelligence (AI) tool using a deep
learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non …

Management of stroke highly depends on informa-tion from imaging studies. Noncontrast
computed tomography (CT) and magnetic resonance imaging (MRI) can both be used to …

Objectives To evaluate the performance of an AI-powered algorithm for the automatic
detection of pulmonary embolism (PE) on chest computed tomography pulmonary …

Background The Alberta Stroke Program Early CT Score (ASPECTS) evaluation is a
qualitative method to evaluate focal hypoattenuation at brain CT in early acute stroke …

Objectives To evaluate and compare the diagnostic performances of a commercialized
artificial intelligence (AI) algorithm for diagnosing pulmonary embolism (PE) on CT …

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