Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty.

The "Crossing Collection Sign": A Diagnostic Tool on Spine Magnetic Resonance Imaging For Localizing Cerebrospinal Fluid Leak.

Objective: The aim of the study is to determine whether the site of "cross" between ventral and dorsal spinal longitudinal extradural CSF collections (SLECs) seen on magnetic resonance imaging during initial workup of patients with suspected CSF leaks can predict the subsequently confirmed leakage site on computed tomography myelography or surgical repair.

Methods: This was an institutional review board-approved, retrospective study performed from 2006 to 2021. Patients with SLECs who underwent total spine magnetic resonance imaging at our institution, followed by myelography and/or surgical repair for CSF leak, were included.

Clinical and neuroradiologic characteristics in varicella zoster virus reactivation with central nervous system involvement.

Objective: To investigate the clinical and magnetic resonance imaging (MRI) characteristics of patients with varicella zoster virus (VZV) reactivation involving the cranial nerves and central nervous system (CNS).

Methods: This is a retrospective, multi-center case-series of 37 patients with VZV infection affecting the cranial nerves and CNS.

Results: The median age was 71 years [IQR 51.

Auditory cues reveal intended movement information in middle frontal gyrus neuronal ensemble activity of a person with tetraplegia.

Intracortical brain-computer interfaces (iBCIs) allow people with paralysis to directly control assistive devices using neural activity associated with the intent to move. Realizing the full potential of iBCIs critically depends on continued progress in understanding how different cortical areas contribute to movement control. Here we present the first comparison between neuronal ensemble recordings from the left middle frontal gyrus (MFG) and precentral gyrus (PCG) of a person with tetraplegia using an iBCI.