ReviewSensors (Basel, Switzerland)2021
Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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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.
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Who cites it
21 citing papers in PubMed.
- The role of "red flags" in the diagnostic work-up of hereditary transthyretin amyloidosis: a study using a machine-learning approach.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Pipettes and Pipelines: The Weapons of Omics Sciences for a New Age of Clinical Studies.Current issues in molecular biology · 2026Review
- A Pressure-Centered Mechanistic Framework for Precision Otology: The Neuro-Vascular-Mechanical-Inflammatory-Autonomic (NVMIA) Regulatory Architecture.Journal of personalized medicine · 2026Review
- Optimizing Dizziness Management: Impact of Audiology Triage on Care Efficiency.The Laryngoscope · 2026Article
- Posterior Fossa Meningioma with Endolymphatic Sac Compression: Resolution of Dizziness after Surgery.Journal of neurological surgery reports · 2026Article
- [The SCD diagnostic strategy, procedure and pathway for episodic vestibular syndrome].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2026Review
- Automated vertigo diagnosis using video-oculography and artificial intelligence for clinic-based triage: Preliminary results.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Can Vascular Vertigo Be Recognized by Artificial Intelligence Methods?Noro psikiyatri arsivi · 2026Article
- Smartphone-based vestibular & gait analysis for remote fall risk assessment.Frontiers in digital health · 2026Article
- Classification of Chronic Dizziness Using Large Language Models.Journal of healthcare informatics research · 2025Article
- Dizziness and vertigo sick leave before and after insurance restrictions - a descriptive Swedish nationwide register linkage study.BMC public health · 2024Article
- Machine learning models help differentiate between causes of recurrent spontaneous vertigo.Journal of neurology · 2024Article
- Comprehensive Equilibrium Function Tests for an Accurate Diagnosis in Vertigo: A Retrospective Analysis.Journal of clinical medicine · 2024Article
- Hemodynamic alterations and their clinical implications in the vertebrobasilar system among patients with isolated posterior circulation ischemic vertigo.Frontiers in neurology · 2024Article
- Neurological update: neuro-otology 2023.Journal of neurology · 2023Article
- Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis.Frontiers in genetics · 2023Article
- Automatic theranostics for long-term neurorehabilitation after stroke.Frontiers in aging neuroscience · 2023Article
- Automated machine learning to predict the difficulty for endoscopic resection of gastric gastrointestinal stromal tumor.Frontiers in oncology · 2023Article
- Development and Validation of the Predictive Model for the Differentiation between Vestibular Migraine and Meniere's Disease.Journal of clinical medicine · 2022Article
- Artificial intelligence for early stroke diagnosis in acute vestibular syndrome.Frontiers in neurology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated only after a correct diagnosis of the underlying vestibular disorder is reached. Recent advances in artificial intelligence promise novel strategies for the diagnosis and treatment of patients with this common symptom. Human analysts may experience difficulties manually extracting patterns from large clinical datasets. Machine learning techniques can be used to visualize, understand, and classify clinical data to create a computerized, faster, and more accurate evaluation of vertiginous disorders. Practitioners can also use them as a teaching tool to gain knowledge and valuable insights from medical data. This paper provides a review of the literatures from 1999 to 2021 using various feature extraction and machine learning techniques to diagnose vertigo disorders. This paper aims to provide a better understanding of the work done thus far and to provide future directions for research into the use of machine learning in vertigo diagnosis.
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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.