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Central Nervous System Diseases

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Determination of CSF GFAP, CCN5, and vWF Levels Enhances the Diagnostic Accuracy of Clinically Defined MS From Non-MS Patients With CSF Oligoclonal Bands.

Frontiers in immunology
BACKGROUND: Inclusion of cerebrospinal fluid (CSF) oligoclonal IgG bands (OCGB) in the revised McDonald criteria increases the sensitivity of diagnosis when dissemination in time (DIT) cannot be proven. While OCGB negative patients are unlikely to de...

Artificial neural networks in neurosurgery.

Journal of neurology, neurosurgery, and psychiatry
Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literatu...

[NEW OPPORTUNITIES IN NEURO-REHABILITATION: ROBOT MEDIATED THERAPY IN CONDITONS POST CENTRAL NERVOUS SYSTEM IMPAIRMENTS].

Ideggyogyaszati szemle
Decreasing the often-seen multiple disabilities as a consequence of central nervous system impairments requires broadening of the tools of rehabilitation. A promising opportunity for this purpose is the application of physiotherapy robots. The develo...

Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders.

European neurology
BACKGROUND: Authors have been advocating the research ideology that a computer-aided diagnosis (CAD) system trained using lots of patient data and physiological signals and images based on adroit integration of advanced signal processing and artifici...

Unsupervised Machine Learning in Pathology: The Next Frontier.

Surgical pathology clinics
Applications of artificial intelligence and particularly deep learning to aid pathologists in carrying out laborious and qualitative tasks in histopathologic image analysis have now become ubiquitous. We introduce and illustrate how unsupervised mach...

Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.

Medicinal research reviews
Neurological disorders significantly outnumber diseases in other therapeutic areas. However, developing drugs for central nervous system (CNS) disorders remains the most challenging area in drug discovery, accompanied with the long timelines and high...

Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19.

Briefings in bioinformatics
Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical trials of vaccines and drugs are currently being conducted around the world; however, till now no effective drug is available for COVID-19. Identification...

Establishment of a 13 genes-based molecular prediction score model to discriminate the neurotoxic potential of food relevant-chemicals.

Toxicology letters
Although many neurotoxicity prediction studies of food additives have been developed, they are applicable in a qualitative way. We aimed to develop a novel prediction score that is described quantitatively and precisely. We examined cell viability, r...