ReviewFrontiers in aging neuroscience2023
The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease.
Review in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Knowledge mapping and research trends of accidental falls in patients with Parkinson's disease from 2003 to 2023: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- The rising tide of frailty in Parkinson's disease: a bibliometric study of global research landscape and emerging trends.Frontiers in neurologyPooled it
- Artificial Intelligence Empowers Physical Therapy for Older Adults: A Perspective.Health science reports · 2026Article
- Current Trends in AI Gait Analysis for the Detection and Assessment of Parkinson's Disease Severity: Systematic Review and Meta-Analysis of Performance Using Logit Transformation.Healthcare (Basel, Switzerland) · 2026Review
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- Physiotherapists' perception of barriers and facilitators to the implementation of digital health interventions: a scoping review.BMC health services research · 2026Article
- The future digital outpatient clinic for movement disorders: from technological innovation to ethical and systemic implementation-a position paper.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Computational Approaches to Neurological Disorder Diagnosis: An In-Depth Review of Current Methods and Future ProspectsCurrent medical imaging · 2026Review
- Multimodal neuroimaging and AI integration in cognitive disorders: advances, challenges, and future directions for precision medicine.Psychoradiology · 2026Review
- AI-Based Gait Analysis System for Rehabilitation: Usability Evaluation of Human-Technology Interaction.JMIR rehabilitation and assistive technologies · 2025Article
- Proceedings of the world summit on parkinson's disease.NPJ Parkinson's disease · 2025Article
- Gait analysis for Parkinson's disease using multiscale entropy.Neurodegenerative disease management · 2025Review
- Review
- Parkinson's Disease Detection via Bilateral Gait Camera Sensor Fusion Using CMSA-Net and Implementation on Portable Device.Sensors (Basel, Switzerland) · 2025Article
- Research on artificial intelligence, machine and deep learning in medicine: global characteristics, readiness, and equity.Globalization and health · 2025Article
- Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.European journal of neurology · 2025Observational
- 80N as the Optimal Assistive Threshold for Wearable Exoskeleton-Mediated Gait Rehabilitation in Parkinson's Disease: A Prospective Biomarker Validation Study.Healthcare (Basel, Switzerland) · 2025Article
- Eye Tracking in Parkinson's Disease: A Review of Oculomotor Markers and Clinical Applications.Brain sciences · 2025Review
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization.PeerJ. Computer science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Parkinson's disease is a neurological disorder that can cause gait disturbance, leading to mobility issues and falls. Early diagnosis and prediction of freeze episodes are essential for mitigating symptoms and monitoring the disease. Objective: This review aims to evaluate the use of artificial intelligence (AI)-based gait evaluation in diagnosing and managing Parkinson's disease, and to explore the potential benefits of this technology for clinical decision-making and treatment support. Methods: A thorough review of published literature was conducted to identify studies, articles, and research related to AI-based gait evaluation in Parkinson's disease. Results: AI-based gait evaluation has shown promise in preventing freeze episodes, improving diagnosis, and increasing motor independence in patients with Parkinson's disease. Its advantages include higher diagnostic accuracy, continuous monitoring, and personalized therapeutic interventions. Conclusion: AI-based gait evaluation systems hold great promise for managing Parkinson's disease and improving patient outcomes. They offer the potential to transform clinical decision-making and inform personalized therapies, but further research is needed to determine their effectiveness and refine their use.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.