This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making
its foray into radiology, a move that is catalysing transformational shifts in the healthcare …

A major focus of academia, industry, and global governmental agencies is to develop and
apply artificial intelligence and other advanced analytical tools to transform health care …

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

The clinical deployment of artificial intelligence (AI) applications in medical imaging is
perhaps the greatest challenge facing radiology in the next decade. One of the main …

Endovascular treatment is a highly effective therapy for acute ischemic stroke due to large
vessel occlusion and has recently revolutionized stroke care. Oftentimes, ischemic core …

This paper provides a comprehensive review of deep learning models for ischemic stroke
lesion segmentation in medical images. Ischemic stroke is a severe neurological disease …

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS).
Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement …

Introduction The increasing availability of data and computing power has made machine
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …

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 …

Background Optimal outcomes after large-vessel occlusion (LVO) stroke are highly
dependent on prompt diagnosis, effective communication, and treatment, making LVO an …