Results 91 to 100 of about 9,340,776 (309)
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
Lessons Learned From a Delayed‐Start Trial of Modafinil for Freezing of Gait in Parkinson's Disease
ABSTRACT Objective Freezing of gait (FOG) in people with Parkinson's disease (PwPD) is debilitating and has limited treatments. Modafinil modulates beta/gamma band activity in the pedunculopontine nucleus (PPN), like PPN deep brain stimulation. We therefore tested the hypothesis that Modafinil would improve FOG in PwPD.
Tuhin Virmani +8 more
wiley +1 more source
Multi-scale 3D Convolution Network for Video Based Person Re-Identification
This paper proposes a two-stream convolution network to extract spatial and temporal cues for video based person Re-Identification (ReID). A temporal stream in this network is constructed by inserting several Multi-scale 3D (M3D) convolution layers into ...
Huang, Tiejun +2 more
core +1 more source
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
Whether from a fall, sports concussion, or even combat injury, there is a critical need to identify when an individual is able to return to play or work following traumatic brain injury (TBI).
Katelynn Ondek +15 more
doaj +1 more source
A Distributed Outstar Network for Spatial Pattern Learning [PDF]
The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes.
Carpenter, Gail A.
core +1 more source
Learning Interpretable Spatial Operations in a Rich 3D Blocks World
In this paper, we study the problem of mapping natural language instructions to complex spatial actions in a 3D blocks world. We first introduce a new dataset that pairs complex 3D spatial operations to rich natural language descriptions that require ...
Bisk, Yonatan +3 more
core +1 more source
Spatial Learning in Dragonflies
Spatial learning is evident in dragonflies on a variety of spatial scales. Mature dragonflies must be able to locate a variety of features in the habitat that are critical to survival and reproduction, including sites for breeding, foraging, roosting, and thermoregulating. In many species, these sites do not coincide in space.
Eason, Perri K, Switzer, Paul V.
openaire +3 more sources
Hippocampal Insulin Resistance Impairs Spatial Learning and Synaptic Plasticity
Insulin receptors (IRs) are expressed in discrete neuronal populations in the central nervous system, including the hippocampus. To elucidate the functional role of hippocampal IRs independent of metabolic function, we generated a model of hippocampal ...
C. Grillo +10 more
semanticscholar +1 more source
ABSTRACT Objective People with epilepsy (PWE) may experience cognitive deficits but fail to undergo formal evaluation. This study compares cognitive status between PWE and healthy controls in the West African Republic of Guinea. Methods A cross‐sectional, case–control study was conducted in sequential recruitment phases (July 2024–July 2025) at Ignace ...
Maya L. Mastick +14 more
wiley +1 more source

