Results 81 to 90 of about 119,702 (338)
Cerebello‐Prefrontal Connectivity Underlying Cognitive Dysfunction in Spinocerebellar Ataxia Type 2
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 2 (SCA2) is a hereditary cerebellar degenerative disorder, with motor and cognitive symptoms. The constellation of cognitive symptoms due to cerebellar degeneration is named cerebellar cognitive affective syndrome (CCAS), which has increasingly been recognized to profoundly impact patients' quality of life;
Ami Kumar +7 more
wiley +1 more source
A hierarchical coding-window model of Parkinson's disease [PDF]
arXiv, 2013 Parkinson's disease is an ongoing challenge to theoretical neuroscience and to medical treatment. During the evolution of the disease, neurodegeneration leads to physiological and anatomical changes that affect the neuronal discharge of the Basal Ganglia to an extent that impairs normal behavioral patterns.
arxiv
Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk‐prediction model incorporating multiple demographic parameters and blood biomarkers to enhance prediction accuracy ...
Hengjun Wan +7 more
wiley +1 more source
Motor skills problems in Parkinson Disease
Journal of Education, Health and Sport, 2017 Parkinson Disease is one of the most common neurodegenerative disease. The average age in which PD occur is 54-58 years but the scientists note that Parkinson Disease can also appear in age of 30 or in age of 80.
Anna Maria Dobosiewicz +4 more
doaj +3 more sources
Successful birth of an IVF baby in a patient with Parkinson′s disease
Journal of Human Reproductive Sciences, 2010 Parkinson′s disease, although rare in young patients, may be encountered in the reproductive age group. We report a rare combination of this disease with infertility, which has not been previously reported.
Asha Baxi +2 more
doaj +1 more source
Determining the severity of Parkinson's disease in patients using a multi task neural network [PDF]
Multimedia Tools and Applications, Volume 83, pages 6077-6092,
2024Parkinson's disease is easy to diagnose when it is advanced, but it is very difficult to diagnose in its early stages. Early diagnosis is essential to be able to treat the symptoms. It impacts on daily activities and reduces the quality of life of both the patients and their families and it is also the second most prevalent neurodegenerative disorder ...
arxiv +1 more source
Home‐Based Tele‐tDCS in Amyotrophic Lateral Sclerosis: Feasibility, Safety, and Preliminary Efficacy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited treatment options. Transcranial direct current stimulation (tDCS) shows promise as a neuromodulatory intervention in various neurological disorders, but its application in ALS, particularly in a remote, home‐based format, remains underexplored.
Sangeetha Madhavan +6 more
wiley +1 more source
Time series analysis of Parkinson's disease, Huntington's disease and Amyotrophic Lateral Sclerosis [PDF]
arXiv, 2013 The aim of this paper is to study the (clinical) time-series data of three diseases with complex dynamics: Parkinson's disease, Huntington's disease and Amyotrophic Lateral Sclerosis. For this purpose, first all of the time series data are embedded in a vector space of suitable dimension and then the correlation dimension of the above mentioned ...
arxiv
An Explainable Machine Learning Model for Early Detection of Parkinson's Disease using LIME on DaTscan Imagery [PDF]
arXiv, 2020 Parkinson's disease (PD) is a degenerative and progressive neurological condition. Early diagnosis can improve treatment for patients and is performed through dopaminergic imaging techniques like the SPECT DaTscan. In this study, we propose a machine learning model that accurately classifies any given DaTscan as having Parkinson's disease or not, in ...
arxiv