AIMC Topic: Parkinson Disease

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Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson's disease using [(123)I]FP-CIT SPECT.

European journal of nuclear medicine and molecular imaging
PURPOSE: The study's objective was to develop diagnostic predictive models using data from two commonly used [(123)I]FP-CIT SPECT assessment methods: region-of-interest (ROI) analysis and whole-brain voxel-based analysis.

Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: a single-blind randomized controlled trial.

Clinical rehabilitation
OBJECTIVE: The main aim was to compare robotic gait training vs. balance training for reducing postural instability in patients with Parkinson's disease. The secondary aim was to compare their effects on the level of confidence during activities of d...

[Progresses on temporal interference electromagnetic stimulation for non-invasive deep brain function modulation].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
This article presents a systematic review of the research progress on temporal interference (TI) electromagnetic stimulation for deep brain function modulation. It first analyzes the fundamental principle of generating low-frequency envelopes through...

The Role of HbA1c in Parkinson's Disease: An Integrative Analysis by Single-Cell, Bulk Transcriptome and Mendelian Randomization.

Molecular neurobiology
Decreased glucose tolerance is recognized as a factor associated with Parkinson's disease (PD) progression, yet the relationship between HbA1c and PD prognosis remains insufficiently explored. Using data from the Integrated Epidemiological Unit (IEU)...

Supervised machine learning and molecular docking modeling to identify potential Anti-Parkinson's agents.

Journal of molecular graphics & modelling
Parkinson's disease is a neurodegenerative condition that affects the brain's neurons, and causes malfunction of nerve cells and their death. A neurotransmitter called dopamine interacts with the part of the brain in charge of coordination and moveme...

Identification of differentially co-expressed genes with lipid metabolism in Parkinson's disease by bioinformatics analysis.

Neuroscience
There was increasing evidence that lipid metabolism disorders played a significant part in the maturation of Parkinson's disease (PD). The purpose of the article was to investigate a significance of lipid metabolism-related genes (LMRGs) in the matur...

ML-STIM: Machine Learning for SubThalamic nucleus Intraoperative Mapping.

Journal of neural engineering
Deep Brain Stimulation (DBS) of the SubThalamic Nucleus (STN) is effective in alleviating motor symptoms in medication-refractory patients with Parkinson's Disease (PD). Intraoperative identification of the STN relies on MicroElectrode Recordings (ME...

Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.

Korean journal of radiology
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...

Predicting metabolite-disease associations based on dynamic adaptive feature learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, the association between metabolites and complex human diseases has increasingly been recognized as a major research focus. Traditional wet-lab experiments are considered time-consuming and labor-intensive, w...

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Journal of neural engineering
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including cognitive impairment. Its diagnosis, which used to be based on clinical assessment, increasingly relies on biomarkers. While electroence...