AIMC Topic: Parkinson Disease

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Enrichment of extracellular vesicles using Mag-Net for the analysis of the plasma proteome.

Nature communications
Extracellular vesicles (EVs) in plasma are composed of exosomes, microvesicles, and apoptotic bodies. We report a plasma EV enrichment strategy using magnetic beads called Mag-Net. Proteomic interrogation of this plasma EV fraction enables the detect...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Scientific reports
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...

Design of a deep fusion model for early Parkinson's disease prediction using handwritten image analysis.

Scientific reports
Parkinson's Disease (PD) is a deteriorating condition that mostly affects older people. The lack of conclusive treatment for PD makes diagnosis very challenging. However, using patterns like tremors for early diagnosis, handwriting analysis has becom...

Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases.

Nature communications
The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieve an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multi...

Explainable classification of Parkinson's disease with different motor subtypes by analyzing the synthetic MRI quantitative parameters of subcortical nuclei.

European journal of radiology
OBJECTIVES: To explore differences in quantitative parameters of subcortical nuclei using synthetic MRI across different motor subtypes of Parkinson's Disease (PD), and to develop an interpretable model for distinguishing PD subtypes.

Your turn: At home turning angle estimation for Parkinson's disease severity assessment.

Artificial intelligence in medicine
People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating tools are not capable of capturing hour-by-hour variations of PD sympto...

Subthalamic nucleus or globus pallidus internus deep brain stimulation for the treatment of parkinson's disease: An artificial intelligence approach.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: Generative artificial intelligence (AI) in deep brain stimulation (DBS) is currently unvalidated in its content. This study sought to analyze AI responses to questions and recommendations from the 2018 Congress of Neurological Surgeons (C...

O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.

Journal of biomechanics
Accurate gait events detection is imperative for reliable assessment of normal and pathological gaits. However, this detection becomes challenging in the absence of force plates. Hence, this research introduces two geometric models integrated into an...

Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.

BMC microbiology
Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disrupted gut microbiota composition and function (dysbiosis) has been found in multiple studies. Thus, h...

The Performance of Biomarkers for the Diagnosis of Parkinson Disease: A Systematic Review.

The American journal of medicine
BACKGROUND: Early diagnosis of Parkinson disease remains challenging due to the current clinical diagnostic approach. With machine learning emerging as a powerful tool for biomarker discovery, we aimed to determine whether biomarkers processed by mac...