Latest AI and machine learning research in parkinson's disease for healthcare professionals.
Parkinsons Disease (PD) is a progressive neurological disorder that primarily affects motor functions and can lead to mild cognitive impairment (MCI) and dementia in its advanced stages. With approximately 10 million people diagnosed globally 1 to 1.8 per 1,000 individuals, according to reports by the Japan Times and the Parkinson Foundation early and accurate diagnosis of PD is crucial for impr...
BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD), elevating the risk of falls substantially. Falls afflict 35% to 90% of PD patients, representing a major challenge in managing the condition. Accurate prediction of fall risk and identification of contributing factors are essential for timely interventions.
Parkinson's disease (PD) remains a condition without a cure, though its early manifestations can be managed effectively by medical professionals. This...
Adaptive deep brain stimulation (aDBS) has emerged as a promising treatment for Parkinson disease (PD). In aDBS, a surgically placed electrode sends...
Predicting disease states from functional brain connectivity is critical for the early diagnosis of severe neurodegenerative diseases such as Alzhei...
The demand for lightweight models in image classification tasks under resource-constrained environments necessitates a balance between computational...
This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature interactions through graph-based explainable AI. Post-s...
Regularization strategies in medical image registration often take a one-size-fits-all approach by imposing uniform constraints across the entire im...
Previous research has established type 2 diabetes mellitus as a significant risk factor for various disorders, adversely impacting human health. While...
Gait analysis is crucial for the diagnosis and monitoring of movement disorders like Parkinson's Disease. While computer vision models have shown po...
Parkinson's disease (PD) is a prevalent neurodegenerative disorder globally. The eye's retina is an extension of the brain and has great potential i...
The five senses are gateways to our wellbeing and their decline is considered a significant public health challenge which is linked to multiple cond...
This study investigates EEG as a potential early biomarker by applying deep learning techniques to resting-state EEG recordings from 31 subjects (15...
This work aims to tackle the Parkinson's disease (PD) detection problem from the speech signal in a bilingual setting by proposing an ad-hoc dual-he...
Motion serves as a powerful cue for scene perception and understanding by separating independently moving surfaces and organizing the physical world...
Journaling plays a crucial role in managing chronic conditions by allowing patients to document symptoms and medication intake, providing essential ...
Background:Speech patterns have emerged as potential diagnostic markers for conditions with varying etiologies. Machine learning (ML) presents an op...
Oculomotor alterations constitute a promising biomarker to detect and characterize Parkinson's disease (PD), even in prodromal stages. Currently, on...
Spontaneous brain activity generically displays transient spatiotemporal coherent structures, which can selectively be affected in various neurologi...
Background: Mutations in KMT2B are a recognized cause of early-onset complex dystonia, with deep brain stimulation (DBS) of the internal globus pall...