ReviewDiagnostics (Basel, Switzerland)2023
Exploring Huntington's Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- Facial expression deep learning algorithms in the detection of neurological disorders: a systematic review and meta-analysis.Biomedical engineering online · 2025Pooled it
- Advancing biomedical data analytics using explainable neural network-based learning model for progressive neurodegenerative disorder diagnosis.Scientific reports · 2026Article
- Systems Biology and Multi-Omics in Asthma and COPD: A Systematic Review of Computational Approaches (2010-2024).Journal of asthma and allergy · 2026Review
- Using voice and speech data in healthcare: a scoping review of the ethical, legal and social implications.Frontiers in digital health · 2026Review
- Computational Approaches to Neurological Disorder Diagnosis: An In-Depth Review of Current Methods and Future ProspectsCurrent medical imaging · 2026Review
- Natural products proposed for the management of Huntington's disease (HD): a comprehensive review.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Glycosphingolipids in Dementia: Insights from Mass Spectrometry and Systems Biology Approaches.Biomedicines · 2025Review
- Evidence based molecular pathways, available drug targets, pre- clinical animal models and future disease modifying treatments of huntington's disease.Molecular biology reports · 2025Review
- Review
- Polymer-Based Electrochemical Sensors for the Diagnosis of Neurodegenerative Diseases.Cellular and molecular neurobiology · 2025Review
- Advances in Huntington's Disease Biomarkers: A 10-Year Bibliometric Analysis and a Comprehensive Review.Biology · 2025Review
- Biological determinants of blood-based biomarker levels in Alzheimer's disease: role of nutrition, inflammation, and metabolic factors.Frontiers in aging neuroscience · 2025Review
- Therapeutic approaches targeting aging and cellular senescence in Huntington's disease.CNS neuroscience & therapeutics · 2024Review
- Brain Volumetric Analysis Using Artificial Intelligence Software in Premanifest Huntington's Disease Individuals from a Colombian Caribbean Population.Biomedicines · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Huntington's Disease (HD) is a devastating neurodegenerative disorder characterized by progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early and accurate diagnosis of HD is crucial for effective intervention and patient care. This comprehensive review provides a comprehensive overview of the utilization of Artificial Intelligence (AI) powered algorithms in the diagnosis of HD. This review systematically analyses the existing literature to identify key trends, methodologies, and challenges in this emerging field. It also highlights the potential of ML and DL approaches in automating HD diagnosis through the analysis of clinical, genetic, and neuroimaging data. This review also discusses the limitations and ethical considerations associated with these models and suggests future research directions aimed at improving the early detection and management of Huntington's disease. It also serves as a valuable resource for researchers, clinicians, and healthcare professionals interested in the intersection of machine learning and neurodegenerative disease diagnosis.
Indexed as
Identifiers
What OpenQuestion holds
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.