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Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders-a comprehensive review / 国际口腔科学杂志·英文版
Article de En | WPRIM | ID: wpr-1010713
Bibliothèque responsable: WPRO
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.
Sujet(s)
Texte intégral: 1 Indice: WPRIM Sujet Principal: Mesure de la douleur / Algie faciale / Intelligence artificielle / Troubles de l'articulation temporomandibulaire / Neuroimagerie Limites du sujet: Humans langue: En Texte intégral: International Journal of Oral Science Année: 2023 Type: Article
Texte intégral: 1 Indice: WPRIM Sujet Principal: Mesure de la douleur / Algie faciale / Intelligence artificielle / Troubles de l'articulation temporomandibulaire / Neuroimagerie Limites du sujet: Humans langue: En Texte intégral: International Journal of Oral Science Année: 2023 Type: Article