Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review
Evolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral disease...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/12/5/1083 |
| _version_ | 1797500451598368768 |
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| author | Sanjeev B. Khanagar Khalid Alfouzan Mohammed Awawdeh Lubna Alkadi Farraj Albalawi Abdulmohsen Alfadley |
| author_facet | Sanjeev B. Khanagar Khalid Alfouzan Mohammed Awawdeh Lubna Alkadi Farraj Albalawi Abdulmohsen Alfadley |
| author_sort | Sanjeev B. Khanagar |
| collection | DOAJ |
| description | Evolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral diseases that have demonstrated phenomenal precision and accuracy in their performance. The aim of this systematic review is to report on the diagnostic accuracy and performance of AI-based models designed for detection, diagnosis, and prediction of dental caries (DC). Eminent electronic databases (PubMed, Google scholar, Scopus, Web of science, Embase, Cochrane, Saudi Digital Library) were searched for relevant articles that were published from January 2000 until February 2022. A total of 34 articles that met the selection criteria were critically analyzed based on QUADAS-2 guidelines. The certainty of the evidence of the included studies was assessed using the GRADE approach. AI has been widely applied for prediction of DC, for detection and diagnosis of DC and for classification of DC. These models have demonstrated excellent performance and can be used in clinical practice for enhancing the diagnostic performance, treatment quality and patient outcome and can also be applied to identify patients with a higher risk of developing DC. |
| first_indexed | 2024-03-10T03:03:05Z |
| format | Article |
| id | doaj.art-a0d9256dd776423aab2ce7bdee17f434 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T03:03:05Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-a0d9256dd776423aab2ce7bdee17f4342023-11-23T10:39:06ZengMDPI AGDiagnostics2075-44182022-04-01125108310.3390/diagnostics12051083Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic ReviewSanjeev B. Khanagar0Khalid Alfouzan1Mohammed Awawdeh2Lubna Alkadi3Farraj Albalawi4Abdulmohsen Alfadley5Preventive Dental Science Department, College of Dentistry, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi ArabiaKing Abdullah International Medical Research Centre, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi ArabiaPreventive Dental Science Department, College of Dentistry, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi ArabiaKing Abdullah International Medical Research Centre, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi ArabiaPreventive Dental Science Department, College of Dentistry, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11426, Saudi ArabiaKing Abdullah International Medical Research Centre, Ministry of National Guard Health Affairs, Riyadh 11481, Saudi ArabiaEvolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral diseases that have demonstrated phenomenal precision and accuracy in their performance. The aim of this systematic review is to report on the diagnostic accuracy and performance of AI-based models designed for detection, diagnosis, and prediction of dental caries (DC). Eminent electronic databases (PubMed, Google scholar, Scopus, Web of science, Embase, Cochrane, Saudi Digital Library) were searched for relevant articles that were published from January 2000 until February 2022. A total of 34 articles that met the selection criteria were critically analyzed based on QUADAS-2 guidelines. The certainty of the evidence of the included studies was assessed using the GRADE approach. AI has been widely applied for prediction of DC, for detection and diagnosis of DC and for classification of DC. These models have demonstrated excellent performance and can be used in clinical practice for enhancing the diagnostic performance, treatment quality and patient outcome and can also be applied to identify patients with a higher risk of developing DC.https://www.mdpi.com/2075-4418/12/5/1083artificial intelligencedental cariesdiagnosisdetectionprediction |
| spellingShingle | Sanjeev B. Khanagar Khalid Alfouzan Mohammed Awawdeh Lubna Alkadi Farraj Albalawi Abdulmohsen Alfadley Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review Diagnostics artificial intelligence dental caries diagnosis detection prediction |
| title | Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review |
| title_full | Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review |
| title_fullStr | Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review |
| title_full_unstemmed | Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review |
| title_short | Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review |
| title_sort | application and performance of artificial intelligence technology in detection diagnosis and prediction of dental caries dc a systematic review |
| topic | artificial intelligence dental caries diagnosis detection prediction |
| url | https://www.mdpi.com/2075-4418/12/5/1083 |
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