ReviewInternational journal of oral science2023
Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders-a comprehensive review.
Review in International journal of oral science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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
17 citing papers in PubMed.
- Temporomandibular Disorders Beyond Orofacial Pain: A Narrative Review of Musculoskeletal, Headache, and Central Nervous System Implications.Medicina (Kaunas, Lithuania) · 2026Review
- Pain-Affective Disorder Comorbidity in the Temporomandibular Disorders: From Mechanistic Insights to Clinical Management.Neuroscience bulletin · 2026Review
- Review
- Functional brain network alterations in a rat model of dental malocclusion.Frontiers in neuroscience · 2026Article
- Applicability of the theory of pain-sensorimotor interactions to orofacial pain and sensorimotor behavior, and implications for orofacial pain research and management.Journal of oral & facial pain and headache · 2025Review
- A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements.Current opinion in anaesthesiology · 2025Review
- Review
- Quo Vadis Temporomandibular Disorders? By 2050, the Global Prevalence of TMD May Approach 44.Journal of clinical medicine · 2025Article
- Article
- Jaw muscle and joint psychophysics-relevance for clinical orofacial pain practice and research. A narrative review.Journal of oral & facial pain and headache · 2025Review
- Neuroplasticity and Pain Perception: Exploring the Complexities of Temporomandibular Disorders.Cureus · 2025Review
- Effect of regional crosstalk between sympathetic nerves and sensory nerves on temporomandibular joint osteoarthritic pain.International journal of oral science · 2025Article
- Article
- Nutritional Strategies for Chronic Craniofacial Pain and Temporomandibular Disorders: Current Clinical and Preclinical Insights.Nutrients · 2024Review
- An Examination of Temporomandibular Joint Disc Displacement through Magnetic Resonance Imaging by Integrating Artificial Intelligence: Preliminary Findings.Medicina (Kaunas, Lithuania) · 2024Article
- Artificial intelligence and machine learning in diagnosing and managing temporomandibular disorders: A systematic review and meta-analysis.Journal of oral biology and craniofacial researchReview
- Biomarkers in orofacial pain conditions: A narrative review.Journal of oral biology and craniofacial researchReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Chronic Painful Temporomandibular Disorders (TMD) are challenging to diagnose and manage due to their complexity and lack of understanding of brain mechanism. In the past few decades' neural mechanisms of pain regulation and perception have been clarified by neuroimaging research. Advances in the neuroimaging have bridged the gap between brain activity and the subjective experience of pain. Neuroimaging has also made strides toward separating the neural mechanisms underlying the chronic painful TMD. Recently, Artificial Intelligence (AI) is transforming various sectors by automating tasks that previously required humans' intelligence to complete. AI has started to contribute to the recognition, assessment, and understanding of painful TMD. The application of AI and neuroimaging in understanding the pathophysiology and diagnosis of chronic painful TMD are still in its early stages. The objective of the present review is to identify the contemporary neuroimaging approaches such as structural, functional, and molecular techniques that have been used to investigate the brain of chronic painful TMD individuals. Furthermore, this review guides practitioners on relevant aspects of AI and how AI and neuroimaging methods can revolutionize our understanding on the mechanisms of painful TMD and aid in both diagnosis and management to enhance patient outcomes.
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.