The Future of Orthodontics: Deep Learning Technologies.
3d imaging
ai-assisted robotic orthodontics
artificial intelligence
deep learning
machine learning
Journal
Cureus
ISSN: 2168-8184
Titre abrégé: Cureus
Pays: United States
ID NLM: 101596737
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
received:
03
03
2024
accepted:
09
06
2024
medline:
11
7
2024
pubmed:
11
7
2024
entrez:
11
7
2024
Statut:
epublish
Résumé
Deep learning has emerged as a revolutionary technical advancement in modern orthodontics, offering novel methods for diagnosis, treatment planning, and outcome prediction. Over the past 25 years, the field of dentistry has widely adopted information technology (IT), resulting in several benefits, including decreased expenses, increased efficiency, decreased need for human expertise, and reduced errors. The transition from preset rules to learning from real-world examples, particularly machine learning (ML) and artificial intelligence (AI), has greatly benefited the organization, analysis, and storage of medical data. Deep learning, a type of AI, enables robots to mimic human neural networks, allowing them to learn and make decisions independently without the need for explicit programming. Its ability to automate cephalometric analysis and enhance diagnosis through 3D imaging has revolutionized orthodontic operations. Deep learning models have the potential to significantly improve treatment outcomes and reduce human errors by accurately identifying anatomical characteristics on radiographs, thereby expediting analytical processes. Additionally, the use of 3D imaging technologies such as cone-beam computed tomography (CBCT) can facilitate precise treatment planning, allowing for comprehensive examinations of craniofacial architecture, tooth movements, and airway dimensions. In today's era of personalized medicine, deep learning's ability to customize treatments for individual patients has propelled the field of orthodontics forward tremendously. However, it is essential to address issues related to data privacy, model interpretability, and ethical considerations before orthodontic practices can use deep learning in an ethical and responsible manner. Modern orthodontics is evolving, thanks to the ability of deep learning to deliver more accurate, effective, and personalized orthodontic treatments, improving patient care as technology develops.
Identifiants
pubmed: 38989357
doi: 10.7759/cureus.62045
pmc: PMC11234326
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
e62045Informations de copyright
Copyright © 2024, Surendran et al.
Déclaration de conflit d'intérêts
Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.