AIMC Topic: Parkinson Disease
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O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.
Journal of biomechanics
Jun 6, 2025
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
Jun 6, 2025
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...
Using machine learning to identify Parkinson's disease severity subtypes with multimodal data.
Journal of neuroengineering and rehabilitation
Jun 2, 2025
BACKGROUND: Classifying and predicting Parkinson's disease (PD) is challenging because of its diverse subtypes based on severity levels. Currently, identifying objective biomarkers associated with disease severity that can distinguish PD subtypes in ...
Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime.
Scientific reports
May 31, 2025
Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques ...
Personalized medication recommendations for Parkinson's disease patients using gated recurrent units and SHAP interpretability.
Scientific reports
May 30, 2025
Managing Parkinson's disease (PD) through medication can be challenging due to varying symptoms and disease duration. This study aims to demonstrate the potential of sequence-by-sequence algorithms in recommending personalized medication combinations...
Decoding dynamic brain networks in Parkinson's disease with temporal attention.
Scientific reports
May 29, 2025
Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurological disorders. Conventional imaging analyses often overlook these subtle events due to computational demands. IMPACT (Integrative Multimodal Pipeli...
An Artificial Intelligence Olfactory-Based Diagnostic Model for Parkinson's Disease Using Volatile Organic Compounds from Ear Canal Secretions.
Analytical chemistry
May 28, 2025
Parkinson's Disease (PD), a frequently diagnosed neurodegenerative condition, poses a major global challenge. Early diagnosis and intervention are crucial for PD treatment. This study proposes a diagnostic model for PD that analyzes volatile organic ...
Personalized prediction of gait freezing using dynamic mode decomposition.
Scientific reports
May 28, 2025
Freezing of gait (FoG) is a common severe gait disorder in patients with advanced Parkinson's disease. The ability to predict the onset of FoG episodes early on allows for timely intervention, which is essential for improving the life quality of pati...
Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.
EBioMedicine
May 27, 2025
BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (PPS) are urgently needed. Based on our recent self-supervised vision foundation model the Shift Window UNET TRansformer (Swin UNETR), which uses clini...
QSPR analysis of physico-chemical and pharmacological properties of medications for Parkinson's treatment utilizing neighborhood degree-based topological descriptors.
Scientific reports
May 15, 2025
Topological indices are invariant quantitative metrics associated with a molecular graph, which characterize the bonding topology of a molecule. The main aim of analyzing topological indices is to summarize and transform chemical structural informati...
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