Results 71 to 80 of about 1,568,688 (370)
PARK: Parkinson's Analysis with Remote Kinetic-tasks [PDF]
arXiv, 2023 We present a web-based framework to screen for Parkinson's disease (PD) by allowing users to perform neurological tests in their homes. Our web framework guides the users to complete three tasks involving speech, facial expression, and finger movements. The task videos are analyzed to classify whether the users show signs of PD.
arxiv
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network [PDF]
arXiv, 2020 This paper presents a novel graph convolutional neural network (GCNN)-based approach for improving the diagnosis of neurological diseases using scalp-electroencephalograms (EEGs). Although EEG is one of the main tests used for neurological-disease diagnosis, the sensitivity of EEG-based expert visual diagnosis remains at $\sim$50\%.
arxiv
Quality improvement in neurology
Neurology, 2018 Epilepsy is a common condition in the United States. It is estimated that 1.2% of the population or 3.4 million people have epilepsy. This figure may be underestimated because of potential repercussions and stigma in disclosing epilepsy.1 Studies have ...
Anup D. Patel +14 more
semanticscholar +1 more source
Exploring Diseases and Syndromes in Neurology Case Reports from 1955 to 2017 with Text Mining [PDF]
arXiv, 2019 Background: A large number of neurology case reports have been published, but it is a challenging task for human medical experts to explore all of these publications. Text mining offers a computational approach to investigate neurology literature and capture meaningful patterns. The overarching goal of this study is to provide a new perspective on case
arxiv
NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics [PDF]
arXiv, 2021 The dominant paradigm for neural text generation is left-to-right decoding from autoregressive language models. Constrained or controllable generation under complex lexical constraints, however, requires foresight to plan ahead feasible future paths. Drawing inspiration from the A* search algorithm, we propose NeuroLogic A*esque, a decoding algorithm
arxiv
, 1996 This book covers broad aspects of clinical neurology necessary fro clinical practice. The organization is unique, starting from patient approach, cardinal manifestations of neurological disease, to specific neruological diseases.
R. Adams, M. Victor
semanticscholar +1 more source
Principles of OCTA and Applications in Clinical Neurology
Current Neurology and Neuroscience Reports, 2018 Purpose of ReviewThe article reviews the recent findings on the use of optical coherence tomography angiography (OCTA) in neurology.Recent FindingsOCTA is a new addition to the powerful and complementary technology of the OCT. Due to its noninvasiveness,
A. Wylęgała
semanticscholar +1 more source
Spectrum of Neurologic Complications in COVID-19: An Evidence-Based Review
Journal of Neuroanaesthesiology and Critical Care, 2020 The world is facing an unprecedented crisis due to the pandemic of current coronavirus disease 2019 (COVID-19). Coronavirus (CoVs) infections not only are always involving the respiratory tract but also possess significant neuroinvasive potential.
Soumya Sarkar +2 more
doaj +1 more source