Latest AI and machine learning research in parkinson's disease for healthcare professionals.
The automatic identification of medication states of Parkinson's disease (PD) patients can assist clinicians in monitoring and scheduling personalized treatments, as well as studying the effects of medication in alleviating the motor symptoms that characterize the disease. This paper explores speech as a non-invasive and accessible biomarker for identifying PD medication states, introducing a no...
In advanced Parkinson's disease (PD), considerable number of patients receive deep brain stimulation (DBS) surgery, to alleviate symptoms not readily controlled by medication. However, the differential effects of medication and DBS on improving motor symptoms, especially for DBS targeting the globus pallidus internus (GPi), have not been explored in sufficient detail. We studied the finger tapping...
BACKGROUND: With the rapid development of digital biomarkers in Parkinson disease (PD) research, it has become increasingly important to explore the c...
Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control ove...
Parkinson's disease (PD) poses a growing global health challenge, with Bangladesh experiencing a notable rise in PD-related mortality. Early detecti...
INTRODUCTION: Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters...
This study explored the perspectives of people with Parkinson's disease (PwP) involved in the co-design of AI tools for PD care. The aim was to unders...
This work presents DLO-Splatting, an algorithm for estimating the 3D shape of Deformable Linear Objects (DLOs) from multi-view RGB images and grippe...
Parkinson's disease (PD) exhibits a variety of symptoms, with approximately 25% of patients experiencing mild cognitive impairment and 45% developing ...
We aimed to develop a convolutional neural network (CNN) model with multi-task learning to predict the onset of levodopa-induced dyskinesia (LID) in p...
This study investigates the classification of individuals as healthy or at risk of Parkinson's disease using machine learning (ML) models, focusing on...
Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impairment of cellular functions. Messenger RNA (mRNA) h...
BACKGROUND: We aimed to use deep learning (DL) techniques to accurately differentiate Parkinson's disease (PD) from multiple system atrophy (MSA), whi...
Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor dysfunctions that severely compromise patients' qua...
BACKGROUND: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder characterized by parkinsonism and impairments in balance, langua...
Parkinson's disease (PD) is a complex neurodegenerative disorder lacking effective disease-modifying treatments. In this study, we integrated large-sc...
Parkinson's disease (PD) is a neurodegenerative disorder, manifesting with motor and non-motor symptoms. Depressive symptoms are prevalent in PD, af...
Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremo...
Deep neural networks have shown potential in analyzing digitized hand-drawn signals for early diagnosis of Parkinson's disease. However, the lack of...
This study investigates whether individuals can learn to accurately discriminate between human-written and AI-produced texts when provided with imme...