- Home
- Medical news & Guidelines
- Anesthesiology
- Cardiology and CTVS
- Critical Care
- Dentistry
- Dermatology
- Diabetes and Endocrinology
- ENT
- Gastroenterology
- Medicine
- Nephrology
- Neurology
- Obstretics-Gynaecology
- Oncology
- Ophthalmology
- Orthopaedics
- Pediatrics-Neonatology
- Psychiatry
- Pulmonology
- Radiology
- Surgery
- Urology
- Laboratory Medicine
- Diet
- Nursing
- Paramedical
- Physiotherapy
- Health news
- AYUSH
- State News
- Andaman and Nicobar Islands
- Andhra Pradesh
- Arunachal Pradesh
- Assam
- Bihar
- Chandigarh
- Chattisgarh
- Dadra and Nagar Haveli
- Daman and Diu
- Delhi
- Goa
- Gujarat
- Haryana
- Himachal Pradesh
- Jammu & Kashmir
- Jharkhand
- Karnataka
- Kerala
- Ladakh
- Lakshadweep
- Madhya Pradesh
- Maharashtra
- Manipur
- Meghalaya
- Mizoram
- Nagaland
- Odisha
- Puducherry
- Punjab
- Rajasthan
- Sikkim
- Tamil Nadu
- Telangana
- Tripura
- Uttar Pradesh
- Uttrakhand
- West Bengal
- Medical Education
- Industry
AI may identify dental implant systems accurately on radiography
![AI may identify dental implant systems accurately on radiography AI may identify dental implant systems accurately on radiography](https://medicaldialogues.in/h-upload/2023/06/06/750x450_211341-1290320222539fig5html.webp)
Artificial intelligence may identify dental implant systems accurately on radiography suggests a new study published in The International Journal of Periodontics & Restorative Dentistry
Health care is entering a new era where data mining is applied to artificial intelligence. The number of dental implant systems has been increasing worldwide. Patient mobility from different dental offices can make identification of implants for clinicians extremely challenging if there are no past available records, and it would be advantageous to use a reliable tool to identify the various implant system designs in the same practice, as there is a great need for identifying the systems in the field of periodontology and restorative dentistry. However, there have not been any studies devoted to using artificial intelligence/convolutional neural networks to classify implant attributes. Thus, the present study used artificial intelligence to identify the attributes of radiographic images of implants. An average accuracy rate of over 95% was achieved with various machine learning networks to identify three implant manufacturers and their subtypes placed during the past 9 years.
This study evaluated the possibility of identifying dental implant systems on radiographs (based on implant attributes) using artificial intelligence (AI)/convolutional neural networks. A 95% accuracy in correctly identifying three implant systems and their subtypes on 657 radiographs was reported. Interface, taper, thread type, apical grooves, and collar were some of the key implant attributes used by the AI program for implant identification.
With numerous dental implant systems available, it sometimes becomes challenging for the clinician to properly identify the implant system, be it for restoration or explantation. In the future, AI-based systems can come in handy and save time for busy clinicians.
Reference:
Chinhua Y. Hsiao, DMD, MS/Hexin Bai, PhD/Haibin Ling, PhD/Jie Yang, DMD, MS
. Artificial Intelligence in Identifying Dental Implant Systems on Radiographs. DOI: 10.11607/prd.5781
Keywords:
AI,identify, dental implant, systems, accurately, radiography, The International Journal of Periodontics & Restorative Dentistry
Dr. Shravani Dali has completed her BDS from Pravara institute of medical sciences, loni. Following which she extensively worked in the healthcare sector for 2+ years. She has been actively involved in writing blogs in field of health and wellness. Currently she is pursuing her Masters of public health-health administration from Tata institute of social sciences. She can be contacted at editorial@medicaldialogues.in.
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: editorial@medicaldialogues.in. Contact no. 011-43720751