Latest AI and machine learning research in parkinson's disease for healthcare professionals.
Due to the late manifestation of structural symptoms and symptomatic overlap, neurodegenerative diseases such as Parkinson's Disease (PD) and Alzheimer's Disease (AD) remain difficult to diagnose accurately. In order to categorize AD and PD in comparison to Healthy Controls (HC), this study suggests a multimodal classification framework that combines genetic Single Nucleotide Polymorphism (SNP) da...
BACKGROUND: Parkinson disease (PD) presents diagnostic challenges due to its heterogeneous motor and nonmotor manifestations. Traditional machine learning (ML) approaches have been evaluated on structured clinical variables. However, the diagnostic utility of large language models (LLMs) using natural language representations of structured clinical data remains underexplored. OBJECTIVE: This study...
BACKGROUND: Dementia and Parkinson's disease (PD) are among the most prevalent neurological disorders globally. Most previous research has focused on ...
We employ coarse-grained molecular dynamics simulations to investigate interfacial reorganization in polymer-nanoparticle composites, focusing on the ...
The application of machine learning (ML) and artificial intelligence (AI) algorithms in medical imaging is an emerging area of interest, particularly ...
BACKGROUND: Action tremor that begins with voluntary movement is a common manifestation of essential tremor (ET). We investigated a novel approach to ...
Quantitative PET imaging requires accurate attenuation and scatter correction (ASC), but the standard CT-based method introduces additional radiation ...
Understanding how land-use change alters the flow of ecosystem services is critical for sustainability policy and planning. We conducted a systematic ...
Brain imaging genetics aims to uncover the pathological mechanisms and improve the diagnosis of brain diseases, particularly neurodegenerative disorde...
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by dopaminergic neuronal loss and α-synuclein pathology, yet the ro...
PURPOSE: To assess machine learning (ML) classifiers trained on harmonised multicentre ¹²³I-mIBG planar scintigraphy for differentiating Parkinson's d...
BACKGROUND: Cognitive impairment is a core non-motor feature of Parkinson's disease (PD). This study aimed to: (1) assess PD patients' performance on ...
Cognitive impairment arising from ischemic stroke, Alzheimer's disease, and Parkinson's disease presents distinct structural and network-level alterat...
OBJECTIVE: This 24-month longitudinal study involving isolated rapid eye movement sleep behavior disorder (iRBD), early-stage Parkinson's disease (PD)...
BACKGROUND: Brain segmentation using structural MRI is effective for identifying regional atrophy in Parkinsonian syndromes. However, clinical validat...
Self-diagnosis-the capacity of a system to detect and correct its own failures-is a defining property of adaptive systems. In the brain, recursive sel...
Pain is a prominent non-motor symptom of Parkinson's disease (PD); it may appear in various levels (elevated or diminished) during waking hours and su...
Robot-assisted deep brain stimulation (DBS) surgical systems in neurosurgery have demonstrated significant advantages in enhancing operative precision...
INTRODUCTION: Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are ur...
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, is marked by dopaminergic neuron loss and α-synuclein aggregation. Alt...