AIMC Topic: Parkinson Disease

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Integrating artificial intelligence and optogenetics for Parkinson's disease diagnosis and therapeutics in male mice.

Nature communications
Parkinson's disease (PD), a progressive neurodegenerative disorder, presents complex motor symptoms and lacks effective disease-modifying treatments. Here we show that integrating artificial intelligence (AI) with optogenetic intervention, termed opt...

Robotic arm vs. stereotactic frame in deep brain stimulation surgery for movement disorders: a retrospective cohort study.

Acta neurochirurgica
BACKGROUND: Recently, robotic arms have been incorporated into the implantation of electrodes for deep brain stimulation (DBS).This study aimed to determine the accuracy of brain electrode placement, initial clinical efficacy, and safety profile of t...

Screening for Parkinson's disease using "computer vision".

PloS one
BACKGROUND: Identifying bradykinesia is crucial for diagnosing Parkinson's disease (PD). Traditionally, the finger-tapping test has been used, relying on subjective assessments by physicians. Computer vision offers a non-contact and cost-effective al...

Screening, identification, and experimental validation of SUMOylation biomarkers in Parkinson's disease.

Hereditas
BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disorder. The role of protein post-translational modifications (PTMs), especially small ubiquitin-like modifier (SUMO) conjugation (SUMOylation), in PD pathogenesis remains unclear. T...

Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

BMC medical informatics and decision making
BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive c...

Stakeholder Perspectives on Trustworthy AI for Parkinson Disease Management Using a Cocreation Approach: Qualitative Exploratory Study.

Journal of medical Internet research
BACKGROUND: Parkinson disease (PD) is the fastest-growing neurodegenerative disorder in the world, with prevalence expected to exceed 12 million by 2040, which poses significant health care and societal challenges. Artificial intelligence (AI) system...

GAN and LSTM-based collaborative tremor classification approach for next generation healthcare system.

Computers in biology and medicine
PURPOSE: To adopt different deep learning (DL) techniques for Essential tremor (ET) and Parkinson's tremor (PST) classification, a collaborative approach to address the misdiagnosis of healthy and PSD patients based on ET and PST's frequency patterns...

Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning.

Scientific reports
Parkinson's disease (PD) is a progressive neurological disorder that impairs movement control, leading to symptoms such as tremors, stiffness, and bradykinesia. Early and accurate PD detection is essential for effective management and improving patie...

Uncovering locomotor learning dynamics in people with Parkinson's disease.

PloS one
Locomotor learning is important for improving gait and balance impairments in people with Parkinson's disease (PD). While PD disrupts neural networks involved in motor learning, there is a limited understanding of how PD influences the time course of...

Perceived social support in the daily life of people with Parkinson's disease: a distinct role and potential classifier.

Scientific reports
Motor outcomes in Parkinson's disease (PD) have long been the primary diagnostic criteria and treatment targets. While non-motor outcomes of PD impact daily well-being, they are rarely targeted by interventions or utilized for classification. Despite...