Machine Learning Model using Eye Movements for the Differential Diagnosis of iPD and Atypical Parkinsonian Syndromes
Objective: To develop a machine learning (ML) model to first between differentiate between healthy controls, idiopathic PD, Atypical Parkinsonian syndromes and then further subclassify as…Electrochemical Sensing for Accurate L-Dopa Detection in Parkinson’s disease
Objective: This study aims to develop a cost-effective, portable electrochemical sensor for real-time L-dopa monitoring in PD patients, addressing the limitations of current detection techniques.…Dopaminometer: A Smartphone-Based Application to Predict Striatal Dopaminergic Deficit in Prodromal and Manifest Parkinson’s disease
Objective: To assess the feasibility of a smartphone-based application (“Dopaminometer”) for predicting abnormal vs. normal dopamine transporter (DaT) scans and dopaminergic ratios in individuals with…Joint Prediction of Motor and Non-motor Deep Brain Stimulation Outcomes using Quantitative Susceptibility Mapping
Objective: To jointly estimate motor and non-motor outcomes of deep brain stimulation using presurgical quantitative susceptibility maps. Background: Parkinson’s disease (PD) patients with motor complications…Impact of Stigma on Patients Diagnosed with Parkinson’s Disease in Buenos Aires (Argentina) : A Descriptive Study of Psychological, Occupational, and Social Dimensions
Objective: To assess the characteristics and impact of stigma in Parkinson’s disease (PD)patients and explore differences by age, gender, education level, and disease duration. Background: Stigma…Detection of novel acoustic biomarkers among Parkinson’s disease patients via an explainable machine learning model
Objective: Our aim was to develop and compare machine learning (ML) algorithms for identification of Parkinson’s disease (PD) patients via acoustic analysis of vowel articulation…Automatic Intelligibility Rating in Parkinson’s Disease: A Multilingual Approach
Objective: To investigate the validity and robustness of an automatically generated intelligibility score in Parkinson’s disease (PD) across multiple languages. Background: 90% of people with…Traditional Deep Brain Stimulation Programming versus Automated Image-Guided Algorithm in Patients with Parkinson’s Disease
Objective: To compare traditional initial deep brain stimulation (DBS) programming with artificial intelligence (AI)-assisted automated image-guided DBS programming algorithm. Background: DBS programming is a complex,…Improved Decision-Making for In-Hospital Medication Management in Parkinson’s Disease
Objective: To enhance clinical decision-making in PD management by developing and validating a conformal prediction framework that forecasts Levodopa Equivalent Daily Dose (LEDD) changes with…Improving Automatic Speech Recognition for Speakers with Parkinson’s disease
Objective: 1. Obtain high-fidelity, speech data from 400 people with Parkinson’s (PWP) to train automatic speech recognition (ASR) systems.2. Develop and implement procedures to recruit,…
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