Neurology

Parkinson's Disease

Latest AI and machine learning research in parkinson's disease for healthcare professionals.

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Integrating bioinformatics and machine learning to uncover lncRNA LINC00269 as a key regulator in Parkinson's disease via pyroptosis pathways.

BACKGROUND: Pyroptosis, a specific type of programmed cell death, which has become a significant fac...

Effectiveness of robot-assisted training in adults with Parkinson's disease: a systematic review and meta-analysis.

AIM: This work aimed to update and summarize the existing evidence on the effectiveness of robot-ass...

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.

Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromu...

Artificial intelligence for identification of candidates for device-aided therapy in Parkinson's disease: DELIST-PD study.

INTRODUCTION: In Parkinson's Disease (PD), despite available treatments focusing on symptom alleviat...

Transformer-based transfer learning on self-reported voice recordings for Parkinson's disease diagnosis.

Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) beca...

Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation.

The application of deep learning techniques for the analysis of neuroimaging has been increasing rec...

Predicting executive functioning from walking features in Parkinson's disease using machine learning.

Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a...

Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning.

Differences in iron accumulation patterns have been observed in susceptibility-weighted images acros...

Deep learning-based denoising for unbiased analysis of morphology and stiffness in amyloid fibrils.

Understanding the morphology of amyloid fibrils is crucial for comprehending the aggregation and deg...

SeeSaw: Learning Soft Tissue Deformation From Laparoscopy Videos With GNNs.

A major challenge in image-guided laparoscopic surgery is that structures of interest often deform a...

Parkinson's disease prediction using improved crayfish optimization based hybrid deep learning.

BackgroundPredicting the course of Parkinson's disease is essential for prompt diagnosis and treatme...

Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity.

Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involunt...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on br...

Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning.

Currently, teleoperated robots, with the operator's input, can fully perceive unknown factors in a c...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Machine learning has gained attention in the medical field. Continuous efforts are being made to dev...

Wearable-Enabled Algorithms for the Estimation of Parkinson's Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors.

Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus...

Deep learning innovations in South Korean maritime navigation: Enhancing vessel trajectories prediction with AIS data.

Predicting ship trajectories can effectively forecast navigation trends and enable the orderly manag...

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