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Artificial Intelligence in Teledentistry

Artificial intelligence (AI) has grown tremendously in the past decade. The application of AI in teledentistry can reform the way dental care, dental education, research, and subsequent innovations can happen remotely. Machine learning including deep learning-based algorithms can be developed to cre...

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Detalles Bibliográficos
Autores principales: Batra, Panchali, Tagra, Himanshu, Katyal, Sakshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Applied Systems srl 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748636/
https://www.ncbi.nlm.nih.gov/pubmed/36530958
http://dx.doi.org/10.15190/d.2022.12
Descripción
Sumario:Artificial intelligence (AI) has grown tremendously in the past decade. The application of AI in teledentistry can reform the way dental care, dental education, research, and subsequent innovations can happen remotely. Machine learning including deep learning-based algorithms can be developed to create predictive models of risk assessment for oral health related conditions, consequent complications, and patient stratification. Patients can be empowered to self-diagnose and apply preventive measures or self-manage some early stages of dental diseases. Applications of AI in teledentistry can be beneficial for both, the dental surgeon and the patient. AI enables better remote screening, diagnosis, record keeping, triaging, and monitoring of dental patients based on smart devices. This will take away rudimentary cases requiring run-of-the-mill treatments from dentists and enable them to concentrate on highly complex cases. This would also enable the dentists to serve a larger and deprived population in inaccessible areas. Its usage in teledentistry can bring a paradigm shift from curative to preventive personalised approach in dentistry. A strong asset to teledentistry could be a robust and comprehensive feedback mechanism routed through various channels proposed in this paper. This paper discusses the application of AI in teledentistry and proposes a feedback mechanism to enhance performance in teledentistry.