Artificial intelligence has the potential to transform dentistry. It can help with tasks like scheduling appointments, taking patient histories, and assisting with diagnoses and treatment planning. AI uses machine learning algorithms that learn from large amounts of dental data to help detect issues in radiographs and identify oral diseases. While AI shows promise in many areas like orthodontics, restorative dentistry, and oral pathology, challenges remain around data privacy, system complexity, and ensuring AI outcomes can be readily applied in clinical practice. Overall, AI aims to enhance the work of dental professionals by allowing for more accurate, consistent analyses and diagnoses, not replace human expertise.

1. SURENDERA DENTAL COLLEGE & RESEARCH INSTITUTE.
Department of Oral Medicine and Radiology
INTER DEPARTMENT MEET 2022

2. Artificial Intelligence
Boon or Curse ….???

3. CONTENT
• Introduction
• History
• Classification
• How does AI work?
• Role of AI in dentistry.
• Current Scenario and Future Prospects
• Conclusion
• References

4. INTRODUCTION

5. Ever since the field of science has originated,
researchers and technologists have been busy in
solving the complexity of the human brain that is a
maze of neurons interconnected with each other and
transmitting signals to the whole body.

6. Artificial intelligence (AI) are machines that are
able to mimic the cognitive functions of humans
to perform tasks of problem-solving and
learning.

7. HISTORY

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Alan Turing (British mathematician, 1936) was one of the most
important visionary and theoretician, proved that a universal
calculator—known as the Turing machine—is possible [13].
Turing’s central insight is that such a machine is capable of solving
any problem as long as it may be represented and solved by an
algorithm.
Newell and Simon (1955) designed “The Logic Theorist” which is
considered to be the first AI program which marks the development
of modern AI.
John McCarthy in 1965 coined the term ‘artificial intelligence

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10. CLASSIFICATION

12. HOW DOES AI
WORK?

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15. Artificial
Intelligence
(AI)
Machine
Learning
1. Genetic algorithms
2. Artificial Neural Networks
(ANN)
3. Fuzzy Logic
Deep
Learning -Subset of ML
-Focus on lines, edges,
corners

16. Machine Learning
 Algorithms are applied to perform tasks by learning patterns from
data.
 Machine learning technique involves parameter adjustment with
regards to underlying technique such as,
o number of neurons,
o layers in a neural network technique;
o population size,
o rate of mutation and
o crossing over rate in genetic algorithms technique etc

17. Deep learning
 A complex multilayer system.
 This system has a complex arrangement of layers and a greater
number of interconnected neurons which makes it capable of
visualizing simple features like
o lines,
o edges,
o corners and
o macroscopic patterns in a hierarchical structure

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Schematic representation of the architecture of neural networks. Artificial neural networks are structures used in machine
learning. They contain many small communicating units called neurons, which are organized in layers. a. Shallow neural
networks are composed of an input layer, a few hidden layers and an output layer. b. Deep neural networks have an input
layer, multiple hidden layers and an output layer. c. Convolutional neural networks use filters to scan a small neighbourhood
of inputs.

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21. Role of Artificial
Intelligence in Dentistry…

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23. AI in general dentistry
 book a patient's appointment in the clinic
 taking proper medical and dental history of the patient
 managing insurance as well as assisting the dental surgeon in adequate
diagnosis and treatment planning
 works by warning the dental professional about the habitual details of
patients like use of tobacco or alcohol and medical history of the patient
 follow up and online emergency health consultancy.

24. Artificial intelligence and diagnostic
dentistry
 Proper diagnosis of any disease is the basis for successful
treatment.
 Example: Internal derangement of temporomandibular joints
where clinical and radiological diagnosis is considered as gold
standard.

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Kim et al. 2009 used Artificial neural network to build a model that can predict
toothache on the basis of association between toothache and daily toothbrushing frequency,
toothbrushing time, use of dental floss, toothbrush replacement pattern, undergoing scaling and
other factors like diet and exercise. This model recognizes adequate eating habits, oral hygiene,
and stress prevention as the most important factors in preventing toothaches

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Nieri et. al 2008 used Bayesian network analysis to identify relationships between various
factors affecting the diagnosis and final treatment outcome of impacted maxillary canines

27. Artificial intelligence
and radiology
 AI provides the additional capability to learn more to be a dental
professional.
 When integrated with imaging methods like MRI and cone beam
computed tomography.
 ML algorithms can detect an abnormal or normal lymph node in
head and neck image.

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30. Artificial intelligence in
Conservative &
Endodontics


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33. Artificial intelligence and
Cosmetic Dentistry
 DSD (Digital smile design)
 DTS Pro (Digital treatment simulation)
 Planmeca Romexis Digital smile design
These software’s make use of AI & ML to help dentist design
smile in a minute.

34. Artificial intelligence and
orthodontics
 3D scans and virtual models are useful in assessing craniofacial and dental
abnormalities
 AI decides how the teeth or tooth of the patients should be moved, how much
pressure should be applied and even also recognize the pressure points for that
specific tooth/teeth.
 The AI conjugated aligners not only provide precise treatment but also reduces
the chances of error and time for treatment.

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38. Artificial intelligence and
restorative/prosthetic dentistry
 provide perfect prosthesis to the patient
 Also, CAD/CAM based systems are used in dentistry to attain finished dental
restorations with great precision.
 3D scans

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42. Artifical intelligence in Oral
Pathology
 Detection and diagnosis of oral lesions is of crucial importance indental practices because
early detection significantly improves prognosis. As some oral lesions can be precancerous or
cancerous in nature, it is important to make an accurate diagnosis and prescribe appropriate
treatment of the patient.
 CNN has been shown to be a promising aid throughout the process of diagnosis of head and
neck cancer lesions. With specificity and accuracy at 78–81.8% and 80–83.3%, respectively
(compared with those of specialists, which were 83.2% and 82.9% respectively), CNN shows
great potential for detecting tumoural tissues in tissue samples or on radiographs.

43. Head and Neck Cancer

44. Artificial intelligence in
periodontics.
 In periodontics AI is used to diagnose the two types of periodontics- Aggressive and
Chronic, which aid in determining the treatment plan to a large extent.
 Papatanopoulos and colleagues have used ANN technology to distinguish between
Aggressive Periodontitis and Chronic types by using immunological parameters such as
Leukocytes, IgG antibody titers, and interleukins.
 ANN was used to identify these parameters which helped in differentiating Aggressive
Periodontitis from Chronic Periodontitis having 90-98% accuracy
S. Sachdeva et al. / Artificial intelligence in periodontics Journal of Cellular
Biotechnology 7 (2021) 119–124

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46. Challenges of AI

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o The management and sharing of clinical data are major challenges in the
implementation of AI systems in health care.
o Personal data from patients are necessary for initial training of AI
algorithms, as well as ongoing training, validation and improvement.
o Furthermore, the development of AI will prompt data sharing among
different institutions and, in some cases, across national boundaries. To
integrate AI into clinical operations, systems must be adapted to protect
patient confidentiality and privacy.

48. Current Scenario
and Future
Prospects

49. The survey by Jaideep Sur et al(2020) of the 250 participating dentists
regarding awareness about artificial intelligence shows following results-

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Benefits of AI in dentistry
 Performing tasks in almost no time.
 Logical and feasible decisions which
results in an accurate diagnosis.
 Procedures can be standardized
Shortcomings of AI use in dentistry
 Mechanism/system complexity
 Costly setup
 Adequate training is required
 Data is often used for both
training and testing, leading to
“data snooping bias”.
 The outcomes of AI in dentistry
are not readily applicable.

56. CONCLUSION

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The AI-powered program helps dental
practitioners analyze radiographs more accurately and
consistently. It doesn’t replace dentists’ expertise but
instead helps them to identify problems and potential
treatments with even greater speed and precision.

58. Bridging the gap to build a better & comfortable future…
THANK YOU.

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