AI Medical Compendium Journal:
Journal of Parkinson's disease

Showing 1 to 8 of 8 articles

Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model.

Journal of Parkinson's disease
BackgroundFreezing of gait (FoG) is a complex, frequent, and disabling motor symptom of Parkinson's disease (PD). Wearable technology has the potential to improve FoG assessment by providing objective, quantitative, and continuous monitoring.Objectiv...

Improving reliability of movement assessment in Parkinson's disease using computer vision-based automated severity estimation.

Journal of Parkinson's disease
BackgroundClinical assessments of motor symptoms rely on observations and subjective judgments against standardized scales, leading to variability due to confounders. Improving inter-rater agreement is essential for effective disease management.Objec...

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

Journal of Parkinson's disease
BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagnosis of IPD. Cardiac autonomic dysfunction begins in the early stages of IPD, and an electrocardiogr...

Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson's Disease?

Journal of Parkinson's disease
The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can...

Video-Based Analyses of Parkinson's Disease Severity: A Brief Review.

Journal of Parkinson's disease
Remote and objective assessment of the motor symptoms of Parkinson's disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the u...

Technology-Based Objective Measures Detect Subclinical Axial Signs in Untreated, de novo Parkinson's Disease.

Journal of Parkinson's disease
BACKGROUND: Technology-based objective measures (TOMs) recently gained relevance to support clinicians in the assessment of motor function in Parkinson's disease (PD), although limited data are available in the early phases.

Quadruple Decision Making for Parkinson's Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine.

Journal of Parkinson's disease
Clinical decision making for Parkinson's disease patients is supported by a combination of three distinct information resources: best available scientific evidence, professional expertise, and the personal needs and preferences of patients. All three...

Automatic Classification on Multi-Modal MRI Data for Diagnosis of the Postural Instability and Gait Difficulty Subtype of Parkinson's Disease.

Journal of Parkinson's disease
BACKGROUND: Patients with the postural instability and gait difficulty subtype (PIGD) of Parkinson's disease (PD) are a refractory challenge in clinical practice. Despite previous attempts that have been made at studying subtype-specific brain altera...