The Use of Artificial Intelligence in Caries Detection: A Review

The Use of Artificial Intelligence in Caries Detection: A Review

Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI t...

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Published in:Bioengineering (Basel) Vol. 11; no. 9; p. 936
Main Authors: Al-Khalifa, Khalifa S, Ahmed, Walaa Magdy, Azhari, Amr Ahmed, Qaw, Masoumah, Alsheikh, Rasha, Alqudaihi, Fatema, Alfaraj, Amal
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 18-09-2024
MDPI
Subjects:
Accuracy
Algorithms
Artificial intelligence
Artificial neural networks
Clinical medicine
Computational linguistics
Datasets
Dental caries
Dental materials
Dentistry
Dentists
detection
Development and progression
diagnosis
Diagnostic tests
Disease prevention
Fluorides
Health aspects
Language processing
Lasers
Morphology
Natural language interfaces
Neural networks
Oral hygiene
Review
Risk assessment
Toiletries industry
treatment planning
dental caries
treatment planning
diagnosis
detection
artificial intelligence
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Abstract Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.
AbstractList Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.
Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This review critically examines the current state of AI applications in caries detection, focusing on the performance and accuracy of various AI techniques. We evaluated 40 studies from the past 23 years, carefully selected for their relevance and quality. Our analysis highlights the potential of AI, especially convolutional neural networks (CNNs), to improve diagnostic accuracy and efficiency in detecting dental caries. The findings underscore the transformative potential of AI in clinical dental practice.
Audience Academic
Author Alfaraj, Amal
Qaw, Masoumah
Alqudaihi, Fatema
Alsheikh, Rasha
Ahmed, Walaa Magdy
Azhari, Amr Ahmed
Al-Khalifa, Khalifa S
AuthorAffiliation 5 Department of Prosthodontics and Dental Implantology, College of Dentistry, King Faisal University, Al-Ahsa 31982, Saudi Arabia; asalfaraj@kfu.edu.sa
4 Department of Restorative Dentistry, Khobar Dental Complex, Eastern Health Cluster, Dammam 32253, Saudi Arabia; fali-alqudaihi@moh.gov.sa
1 Department of Preventive Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia
3 Department of Restorative Dental Sciences, College of Dentistry, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia; mssqaw@iau.edu.sa (M.Q.); ralsheikh@iau.edu.sa (R.A.)
2 Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah 21589, Saudi Arabia; wmahmed@kau.edu.sa (W.M.A.); aaaazhari@kau.edu.sa (A.A.A.)
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– name: 2 Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah 21589, Saudi Arabia; wmahmed@kau.edu.sa (W.M.A.); aaaazhari@kau.edu.sa (A.A.A.)
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Keywords dental caries
treatment planning
diagnosis
detection
artificial intelligence
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Snippet Advancements in artificial intelligence (AI) have significantly impacted the field of dentistry, particularly in diagnostic imaging for caries detection. This...
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SubjectTerms Accuracy
Algorithms
Artificial intelligence
Artificial neural networks
Clinical medicine
Computational linguistics
Datasets
Dental caries
Dental materials
Dentistry
Dentists
detection
Development and progression
diagnosis
Diagnostic tests
Disease prevention
Fluorides
Health aspects
Language processing
Lasers
Morphology
Natural language interfaces
Neural networks
Oral hygiene
Review
Risk assessment
Toiletries industry
treatment planning
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Title The Use of Artificial Intelligence in Caries Detection: A Review
URI https://www.ncbi.nlm.nih.gov/pubmed/39329679
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