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Parkinson Disease

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MRI classification of progressive supranuclear palsy, Parkinson disease and controls using deep learning and machine learning algorithms for the identification of regions and tracts of interest as potential biomarkers.

Computers in biology and medicine
BACKGROUND: Quantitative magnetic resonance imaging (MRI) analysis has shown promise in differentiating neurodegenerative Parkinsonian syndromes and has significantly advanced our understanding of diseases like progressive supranuclear palsy (PSP) in...

Artificial intelligence for identification of candidates for device-aided therapy in Parkinson's disease: DELIST-PD study.

Computers in biology and medicine
INTRODUCTION: In Parkinson's Disease (PD), despite available treatments focusing on symptom alleviation, the effectiveness of conventional therapies decreases over time. This study aims to enhance the identification of candidates for device-aided the...

Transformer-based transfer learning on self-reported voice recordings for Parkinson's disease diagnosis.

Scientific reports
Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) because they offer non-invasive and easily accessible tools. By using advanced data analysis, these methods improve early detection and diagnosis, which i...

Predicting executive functioning from walking features in Parkinson's disease using machine learning.

Scientific reports
Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and ...

Learning Motion Primitives for the Quantification and Diagnosis of Mobility Deficits.

IEEE transactions on bio-medical engineering
The severity of mobility deficits is one of the most critical parameters in the diagnosis of Parkinson's disease (PD) and rehabilitation. The current approach for severity evaluation is clinical scaling that relies on a clinician's subjective observa...

Parkinson's disease prediction using improved crayfish optimization based hybrid deep learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundPredicting the course of Parkinson's disease is essential for prompt diagnosis and treatment, which may enhance patient outcomes.ObjectiveThis study presents a novel method for Parkinson's disease prediction using freely accessible resource...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on brain magnetic resonance imaging (MRI) is significant in assisting the diagnosis of PD. However, due to the degenerative-induced changes in appearance, ...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Scientific reports
Machine learning has gained attention in the medical field. Continuous efforts are being made to develop robust models for early prognosis purposes. The brain is the most pivotal organ in the human body. A brain stroke is generally caused by a blocka...

Development and validation of a machine learning-based diagnostic model for Parkinson's disease in community-dwelling populations: Evidence from the China health and retirement longitudinal study (CHARLS).

Parkinsonism & related disorders
BACKGROUND: Parkinson's disease (PD) is a major neurodegenerative disorder in Middle-aged and elderly people.There is a pressing need for effective predictive models, particularly in chinese population.

Wearable-Enabled Algorithms for the Estimation of Parkinson's Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus, the ideal home monitoring system should be capable of tracking symptoms continuously despite background noise from daily activities. The goal of thi...