Results 181 to 190 of about 136,000 (320)
Our winter birds, how to know and how to attract them,
Frank M. Chapman
openalex +2 more sources
Abstract Purpose This study aims to develop a CycleGAN based denoising model to enhance the quality of low‐dose PET (LDPET) images, making them as close as possible to standard‐dose PET (SDPET) images. Methods Using a Philips Vereos PET/CT system, whole‐body PET images of fluorine‐18 fluorodeoxyglucose (18F‐FDG) were acquired from 37 patients to ...
Yang Liu, ZhiWu Sun, HaoJia Liu
wiley +1 more source
Abstract Purpose/objective We propose a novel lattice deployment for spatially fractionated radiotherapy (SFRT) treatments. In this approach, a larger diameter high‐dose sphere is centrally placed in the bulky tumor mass and surrounded by smaller diameter high‐dose spheres.
Joshua Misa+2 more
wiley +1 more source
Dysphagia and Mortality Risk in Individuals With Primary Progressive Apraxia of Speech
ABSTRACT Individuals with primary progressive apraxia of speech (PPAOS) often develop parkinsonism and dysphagia. To evaluate the clinical correlates and impact of dysphagia in this population, we compared enrollment visit data between individuals with (n = 12) versus individuals without (n = 44) dysphagia symptoms.
Gabriela Meade+8 more
wiley +1 more source
Convolutions of Distributions Attracted to Stable Laws [PDF]
Howard G. Tucker
openalex +1 more source
ABSTRACT Dopaminergic medication and deep brain stimulation (DBS) improve motor symptoms in Parkinson's disease (PD), but levodopa response alone may not predict DBS outcomes. We retrospectively analyzed 19 PD patients undergoing levodopa challenges with and without prior transcranial direct current stimulation targeting a defined PD response network ...
Lukas L. Goede+3 more
wiley +1 more source
An open problem: Why are motif-avoidant attractors so rare in asynchronous Boolean networks? [PDF]
Pastva S+4 more
europepmc +1 more source
Precision‐Optimised Post‐Stroke Prognoses
ABSTRACT Background Current medicine cannot confidently predict who will recover from post‐stroke impairments. Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known.
Thomas M. H. Hope+4 more
wiley +1 more source