STAIR XII (12th Stroke Treatment Academy Industry Roundtable) included a workshop to
discuss the priorities for advancements in neuroimaging in the diagnostic workup of acute …

Background The surge in emergency head CT imaging and artificial intelligence (AI)
advancements, especially deep learning (DL) and convolutional neural networks (CNN) …

Background Outlining acutely infarcted tissue on non-contrast CT is a challenging task for
which human inter-reader agreement is limited. We explored two different methods for …

Stroke is the second leading cause of mortality worldwide. Immediate attention and
diagnosis play a crucial role regarding patient prognosis. The key to diagnosis consists in …

Stroke, the second leading cause of mortality globally, predominantly results from ischemic
conditions. Immediate attention and diagnosis, related to the characterization of brain …

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite
patient management. Most ML algorithms for diagnostic imaging analysis utilize …

Stroke lesion volume is a key radiologic measurement for assessing the prognosis of Acute
Ischemic Stroke (AIS) patients, which is challenging to be automatically measured on Non …

In the last years, we have seen a dramatic increase in the use of brain perfusion imaging in
suspected stroke patients. This increase has taken place since the publication of multiple …

Background Deep learning using clinical and imaging data may improve pre-treatment
prognostication in ischemic stroke patients undergoing endovascular thrombectomy (EVT) …

Globally, many healthcare institutions have adopted interventions related to digital health
technologies to ensure the seamless experience for both patients and clients. Digital health …