• Users Online: 235
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
Year : 2020  |  Volume : 11  |  Issue : 4  |  Page : 175-179

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

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
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijor.ijor_35_20

Rights and Permissions

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.

Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)

 Article Access Statistics
    PDF Downloaded347    
    Comments [Add]    
    Cited by others 3    

Recommend this journal