… Tuladhar A., Gill S., Ismail Z., and Forkert ND 2020. Building machine learning models without
sharing patient data: A simulation-based analysis of distributed learning by ensembling. J. …

In an increasingly data-driven world, artificial intelligence is expected to be a key tool for
converting big data into tangible benefits and the healthcare domain is no exception to this. …

Background Many patients with stroke are precluded from thrombolysis treatment because
the time from onset of their symptoms is unknown. We aimed to test whether a mismatch in …

Background and Purpose— In the early days after ischemic stroke, information on structural
brain damage from MRI supports prognosis of functional outcome. It is rated widely by the …

We present DeepVesselNet, an architecture tailored to the challenges faced when extracting
vessel trees and networks and corresponding features in 3-D angiographic volumes using …

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 …

The fast and accurate assessment of cerebral perfusion is fundamental for the diagnosis and
successful treatment of stroke patients. Magnetic particle imaging (MPI) is a new radiation-…

Motivation Ischemic stroke, triggered by an obstruction in the cerebral blood supply, leads to
infarction of the affected brain tissue. An accurate and reproducible automatic segmentation …

Background and Purpose— Among patients with acute ischemic stroke, we determine computed
tomographic perfusion (CTP) thresholds associated with follow-up infarction at different …

Background: Mild behavioral impairment (MBI) and subjective cognitive decline (SCD) are
dementia risk states, and potentially represent neurobehavioral and neurocognitive …