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Antiparkinson Agents

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A machine learning and network framework to discover new indications for small molecules.

PLoS computational biology
Drug repurposing, identifying novel indications for drugs, bypasses common drug development pitfalls to ultimately deliver therapies to patients faster. However, most repurposing discoveries have been led by anecdotal observations (e.g. Viagra) or ex...

Performance of Force-Field- and Machine Learning-Based Scoring Functions in Ranking MAO-B Protein-Inhibitor Complexes in Relevance to Developing Parkinson's Therapeutics.

International journal of molecular sciences
Monoamine oxidase B (MAOB) is expressed in the mitochondrial membrane and has a key role in degrading various neurologically active amines such as benzylamine, phenethylamine and dopamine with the help of Flavin adenine dinucleotide (FAD) cofactor. T...

Using machine learning-based analytics of daily activities to identify modifiable risk factors for falling in Parkinson's disease.

Parkinsonism & related disorders
BACKGROUND: Although risk factors that lead to falling in Parkinson's disease (PD) have been previously studied, the established predictors are mostly non-modifiable. A novel method for fall risk assessment may provide more insight into preventable h...

Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without c...

An Artificial Neural Network Predicts Gender Differences of Motor and Non-Motor Symptoms of Patients with Advanced Parkinson's Disease under Levodopa-Carbidopa Intestinal Gel.

Medicina (Kaunas, Lithuania)
: Currently, no tool exists to predict clinical outcomes in patients with advanced Parkinson's disease (PD) under levodopa-carbidopa intestinal gel (LCIG) treatment. The aim of this study was to develop a novel deep neural network model to predict th...

Adoption of deep learning-based magnetic resonance image information diagnosis in brain function network analysis of Parkinson's disease patients with end-of-dose wearing-off.

Journal of neuroscience methods
OBJECTIVE: this study was to analyze the brain functional network of end-of-dose wearing-off (EODWO) in patients with Parkinson's disease (PD) using a convolutional neural network (CNN)-based functional magnetic resonance imaging (fMRI) data classifi...

Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.

Parkinsonism & related disorders
BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stag...

Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa response (LR). Assessment of Movement Disorder Society's Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) is a key step in ALCT, which...

Drug repositioning for Parkinson's disease: An emphasis on artificial intelligence approaches.

Ageing research reviews
Parkinson's disease (PD) is one of the most incapacitating neurodegenerative diseases (NDDs). PD is the second most common NDD worldwide which affects approximately 1-2 percent of people over 65 years. It is an attractive pursuit for artificial intel...

Optimizing Neuroprotective Nano-structured Lipid Carriers for Transdermal Delivery through Artificial Neural Network.

Pharmaceutical nanotechnology
BACKGROUND: Dementia associated with Alzheimer's disease (AD) is a neurological disorder. AD is a progressive neurodegenerative condition that predominantly impacts the elderly population, although it can also manifest in younger people through the i...