Latest AI and machine learning research in parkinson's disease for healthcare professionals.
Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. DNA repair dysfunction and integrated stress response (ISR) dysregulation have been suggested to be relevant in PD pathophysiology, but their role during the prodromal phase, before motor symptoms manifest, remains unclear. In this study, we analyzed longitudinal blood transcriptomic...
This research introduces a comprehensive framework for Parkinson’s Disease (PD) detection using voice recording data. We implemented and evaluated multiple deep learning models, including a baseline Convolutional Neural Network (CNN), an uncertainty-aware Monte Carlo-Dropout CNN (MCD-CNN), as well as a few-shot learning approach to address dataset size limitations. Our models achieved an accuracy ...
Programming deep brain stimulation (DBS) of the subthalamic nucleus for optimal symptom control in Parkinson’s Disease (PD) requires time and trained ...
Many neurological conditions negatively affect a person’s walking quality, which is a vital aspect of their quality of life. Gait quality, through the...
Understanding the relevance of covert cerebrovascular disease (CCD) for later health will allow clinicians to more effectively monitor and target inte...
Impulse control disorders (ICD) in Parkinson’s disease (PD) patients mainly occur as adverse effects of dopamine replacement therapy. Despite several ...
Large Language Models (LLMs) offer promising applications in healthcare, including drafting referral letters. However, access to LLMs specifically des...
Video annotation is the gold-standard method to assess Freezing of Gait (FOG) in Parkinsonian disorders, but it is time-consuming. Deep learning (DL)-...
Optimisation of Deep Brain Stimulation (DBS) settings is a key aspect in achieving clinical efficacy in movement disorders, such as the Parkinson’s di...
Parkinson’s Disease (PD) is the second most common neurodegenerative disorder globally, and current screening methods often rely on subjective evaluat...
Parkinson’s disease (PD) remains incurable, with a long preclinical phase currently undetectable by existing methods. In the largest proteomic study i...
Patients with Parkinson’s disease (PD) frequently exhibit deficits in functional communication due to the presence of speech disorders associated with...
Fractional anisotropy (FA) derived from diffusion MRI is a widely used marker of white matter (WM) integrity. However, conventional FA-based genetic s...
Chronic pain is a major healthcare problem associated with maladaptive brain circuit changes - many patients are unresponsive to all available therapi...
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic ph...
Alzheimer’s and Parkinson’s diseases are age-related neurodegenerative diseases that often require invasive procedures for diagnosis. Traditional diag...
Progressive supranuclear palsy (PSP) is typically characterized by vertical supranuclear gaze palsy and early falls, referred to as Richardson’s syndr...
This paper presents the Neurobiome Navigator, an AI-powered, highly interactive, and easily navigable application designed to help users explore the c...
Self-supervised pre-trained speech models such as wav2vec 2.0 provide rich frame-level embeddings that are increasingly used for clinical voice screen...
Parkinson’s disease lacks reliable early diagnostics and disease-modifying treatments. Blood-based biomarkers can facilitate early detection, symptom ...