Parkinson's Disease

Explainable 3D CNNs link regional and network level disruption in early Parkinson’s MRIs to symptom progression

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder affecting approximately 1% of the population over 65. Clinical diagnosis typically depends on tracking gradually developing motor symptoms as the disease progresses, underscoring the need for early detection methods to aid intervention while symptoms are still minor. Inexpensive and widely available imaging modalities such as T1-...

Cross-species etiologically informed stratification enables T cell receptor-based diagnosis of Parkinson’s Disease

Developing peripheral blood-based diagnostic models for idiopathic Parkinson’s disease (iPD), particularly those leveraging the T-cell receptor (TCR) repertoire, has long been considered infeasible because patient-derived TCRs appear to lack convergent sequence motifs. We reasoned that this apparent absence of shared TCR features likely reflects both insufficient sample sizes and unaccounted immun...

Dopamine and serotonin transients predict depressive symptom relief following deep brain stimulation of human subcallosal cingulate cortex

Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depr...

Exploring Stress-Induced Neural Circuit Remodeling through Data-Driven Analysis and Artificial Neural Network Simulation

Chronic stress induces behavioral rigidity and neural circuit remodeling, yet the underlying computational mechanisms remain unclear. In this study, w...

Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer’s, Parkinson’s and dementia at age 65: a study using medical records from France and the UK General Practitioners

Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...

Combining Clinical Embeddings with Multi-Omic Features for Improved Patient Classification and Interpretability in Parkinson’s Disease

This study demonstrates the integration of Large Language Model (LLM)-derived clinical text embeddings from the Movement Disorder Society Unified Park...

Predicting Dementia in People with Parkinson’s Disease

Parkinson’s disease (PD) exhibits a variety of symptoms, with approximately 25% of patients experiencing mild cognitive impairment and 45% developing ...

Machine learning differentiation of Parkinson’s disease and normal pressure hydrocephalus using wearable sensors capturing gait impairments

Gait impairments in patients with Parkinson’s Disease (PD) and Normal Pressure Hydrocephalus (NPH) are diagnosed with visual clinical assessments. Des...

Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson’s Disease

Deep Brain Stimulation (DBS) is an invasive procedure used to alleviate motor symptoms in Parkinson’s Disease (PD) patients. While brain activity can ...

Quantifying Device Type and Handedness Biases in a Remote Parkinson’s Disease AI-Powered Assessment

Early detection of Parkinson’s Disease (PD) can enable early access to care, improving patient outcomes. We investigate the use of machine learning to...

Ranking Pretrained Speech Embeddings in Parkinson’s Disease Detection: Does Wav2Vec 2.0 Outperform its 1.0 Version Across Speech Modes and Languages?

Speech and language technologies are effective tools for identifying the distinct speech changes associated with Parkinson’s disease (PD), enabling ea...

At-Home Movement State Classification Using Totally Implantable Bidirectional Cortical-Basal Ganglia Neural Interface

Movement decoding from invasive human recordings typically relies on a distributed system employing advanced machine learning algorithms programmed in...

Comparative Medical Ecology of Gut Microbiomes in Major Neurodegenerative, Neurodevelopmental, and Psychiatric (NNP) Disorders

This study provides a comprehensive medical ecology analysis of gut microbiome alterations in four neuropsychiatric disorders: Alzheimer’s disease (AD...

Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients with Parkinson’s disease (PD). The adaptive DBS app...

A Pilot Study Comparing Speech Characteristics in People with Parkinson’s Disease and Controls Dancing Weekly Over 5-years

Parkinson’s Disease (PD) is a neurodegenerative disorder that affects motor and non-motor functions. Speech impairments, such as reduced variability i...

Deep Learning Analysis of Figure Copying Tasks for Parkinson’s Disease Detection with GAN-Based Data Augmentation

Early and accurate diagnosis of Parkinson’s disease (PD) is essential for enabling timely treatment and effective disease management. In this study, w...

Silencer variants are key drivers of gene upregulation in Alzheimer’s disease

Alzheimer’s disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative disorder globally. Owing to its substantial herit...

Feasibility of Machine Learning Analysis for the Identification of Patients with Possible Primary Ciliary Dyskinesia

Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening ...

Evaluating the Potential of AI-Generated Synthetic Diaries in Parkinson’s Disease Research

The integration of Artificial Intelligence (AI), particularly large language models like GPT-4o, into Parkinson’s Disease (PD) research presents a nov...

Probabilistic Mapping and Automated Segmentation of Human Brainstem White Matter Bundles

Brainstem white matter bundles are essential conduits for neural signaling involved in modulation of vital functions ranging from homeostasis to human...