International Journal of Orthodontic Rehabilitation

REVIEW ARTICLE
Year
: 2020  |  Volume : 11  |  Issue : 4  |  Page : 175--179

Artificial intelligence and machine learning: The new paradigm in orthodontic practice


V Ganesh Shetty1, Rohan Rai2, K Nillan Shetty2 
1 Consultant Orthodontist, Department of Orthodontics and Dentofacial Orthopedics, Mangalore, Karnataka, India
2 Department of Orthodontics, A J Institute of Dental Sciences, Mangalore, Karnataka, India

Correspondence Address:
Dr. V Ganesh Shetty
A J Institute of Dental Sciences, Mangalore, Karnataka
India

Artificial intelligence (AI) and machine learning (ML) are powerful tools that can be utilized to overcome some of the clinical problems that orthodontists face daily. With the availability of more data, better AI and ML systems should be expected to be developed that will help orthodontists to practise more efficiently and improve the quality of care. AI is a subfield of computer science concerned with developing computers and programs that have the ability to perceive information and reason, and ultimately, convert that information into intelligent actions. The future may be purely digitized, at the comforts of our home, with orthodontists developing neural programs with orthodontic decision markers to aid in developing AI for patients to take less visits, make more use of their time using orthodontic appliances, and enhance the quality of work. This article will briefly discuss the contributions AI and ML in orthodontics, its history and various uses in orthodontics in specific, and the possibility of development.


How to cite this article:
Shetty V G, Rai R, Shetty K N. Artificial intelligence and machine learning: The new paradigm in orthodontic practice.Int J Orthod Rehabil 2020;11:175-179


How to cite this URL:
Shetty V G, Rai R, Shetty K N. Artificial intelligence and machine learning: The new paradigm in orthodontic practice. Int J Orthod Rehabil [serial online] 2020 [cited 2021 Apr 21 ];11:175-179
Available from: https://www.orthodrehab.org/article.asp?issn=2349-5243;year=2020;volume=11;issue=4;spage=175;epage=179;aulast=Shetty;type=0