Applications of artificial intelligence in dentistry: A comprehensive review
Objective To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dent...
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| Veröffentlicht in: | Journal of esthetic and restorative dentistry 2022-01, Vol.34 (1), p.259-280 |
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| container_title | Journal of esthetic and restorative dentistry |
| container_volume | 34 |
| creator | Carrillo‐Perez, Francisco Pecho, Oscar E. Morales, Juan Carlos Paravina, Rade D. Della Bona, Alvaro Ghinea, Razvan Pulgar, Rosa Pérez, María del Mar Herrera, Luis Javier |
| description | Objective
To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research.
Materials and methods
The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years.
Results
Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling.
Conclusions
The insight provided by the present work has reported outstanding results in the design of high‐performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations.
Clinical significance
The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures. |
| doi_str_mv | 10.1111/jerd.12844 |
| format | Article |
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To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research.
Materials and methods
The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years.
Results
Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling.
Conclusions
The insight provided by the present work has reported outstanding results in the design of high‐performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations.
Clinical significance
The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.</description><identifier>ISSN: 1496-4155</identifier><identifier>EISSN: 1708-8240</identifier><identifier>DOI: 10.1111/jerd.12844</identifier><identifier>PMID: 34842324</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Artificial Intelligence ; Color ; Deep learning ; Dentistry ; Forecasting ; Fuzzy logic ; Humans ; Image processing ; Learning algorithms ; Machine Learning ; Segmentation</subject><ispartof>Journal of esthetic and restorative dentistry, 2022-01, Vol.34 (1), p.259-280</ispartof><rights>2021 The Authors. published by Wiley Periodicals LLC.</rights><rights>2021 The Authors. Journal of Esthetic and Restorative Dentistry published by Wiley Periodicals LLC.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5004-d092354f41e70035b0c3ac6225dd4165741ce6dea7e894938aa21d7c6b1efac13</citedby><cites>FETCH-LOGICAL-c5004-d092354f41e70035b0c3ac6225dd4165741ce6dea7e894938aa21d7c6b1efac13</cites><orcidid>0000-0003-0974-4092 ; 0000-0002-8459-5528 ; 0000-0002-8312-7503 ; 0000-0001-8865-2430 ; 0000-0001-7314-5049</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjerd.12844$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjerd.12844$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34842324$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Carrillo‐Perez, Francisco</creatorcontrib><creatorcontrib>Pecho, Oscar E.</creatorcontrib><creatorcontrib>Morales, Juan Carlos</creatorcontrib><creatorcontrib>Paravina, Rade D.</creatorcontrib><creatorcontrib>Della Bona, Alvaro</creatorcontrib><creatorcontrib>Ghinea, Razvan</creatorcontrib><creatorcontrib>Pulgar, Rosa</creatorcontrib><creatorcontrib>Pérez, María del Mar</creatorcontrib><creatorcontrib>Herrera, Luis Javier</creatorcontrib><title>Applications of artificial intelligence in dentistry: A comprehensive review</title><title>Journal of esthetic and restorative dentistry</title><addtitle>J Esthet Restor Dent</addtitle><description>Objective
To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research.
Materials and methods
The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years.
Results
Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling.
Conclusions
The insight provided by the present work has reported outstanding results in the design of high‐performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations.
Clinical significance
The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.</description><subject>Artificial Intelligence</subject><subject>Color</subject><subject>Deep learning</subject><subject>Dentistry</subject><subject>Forecasting</subject><subject>Fuzzy logic</subject><subject>Humans</subject><subject>Image processing</subject><subject>Learning algorithms</subject><subject>Machine Learning</subject><subject>Segmentation</subject><issn>1496-4155</issn><issn>1708-8240</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNp90E1Lw0AQBuBFFFurF3-ABLyIEN2P2U3irdT6RUEQPYftZqJb0iTupi39925t9eDBuewsPLwMLyGnjF6xMNczdMUV4ynAHumzhKZxyoHuhx0yFQOTskeOvJ9RymSSJYekJyAFLjj0yWTYtpU1urNN7aOmjLTrbGmN1VVk6w6ryr5jbTB8ogLrzvrOrW-iYWSaeevwA2tvlxg5XFpcHZODUlceT3bvgLzdjV9HD_Hk-f5xNJzERlIKcUEzLiSUwDChVMgpNUIbxbksCmBKJsAMqgJ1gmkGmUi15qxIjJoyLLVhYkAutrmtaz4X6Lt8br0Jt-oam4XPuaIASgklAz3_Q2fNwtXhuqAEZ8BTmQV1uVXGNd47LPPW2bl265zRfNNxvuk4_-444LNd5GI6x-KX_pQaANuCla1w_U9U_jR-ud2GfgHsooYA</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Carrillo‐Perez, Francisco</creator><creator>Pecho, Oscar E.</creator><creator>Morales, Juan Carlos</creator><creator>Paravina, Rade D.</creator><creator>Della Bona, Alvaro</creator><creator>Ghinea, Razvan</creator><creator>Pulgar, Rosa</creator><creator>Pérez, María del Mar</creator><creator>Herrera, Luis Javier</creator><general>John Wiley & Sons, Inc</general><general>Blackwell Publishing Ltd</general><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0974-4092</orcidid><orcidid>https://orcid.org/0000-0002-8459-5528</orcidid><orcidid>https://orcid.org/0000-0002-8312-7503</orcidid><orcidid>https://orcid.org/0000-0001-8865-2430</orcidid><orcidid>https://orcid.org/0000-0001-7314-5049</orcidid></search><sort><creationdate>202201</creationdate><title>Applications of artificial intelligence in dentistry: A comprehensive review</title><author>Carrillo‐Perez, Francisco ; Pecho, Oscar E. ; Morales, Juan Carlos ; Paravina, Rade D. ; Della Bona, Alvaro ; Ghinea, Razvan ; Pulgar, Rosa ; Pérez, María del Mar ; Herrera, Luis Javier</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5004-d092354f41e70035b0c3ac6225dd4165741ce6dea7e894938aa21d7c6b1efac13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial Intelligence</topic><topic>Color</topic><topic>Deep learning</topic><topic>Dentistry</topic><topic>Forecasting</topic><topic>Fuzzy logic</topic><topic>Humans</topic><topic>Image processing</topic><topic>Learning algorithms</topic><topic>Machine Learning</topic><topic>Segmentation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Carrillo‐Perez, Francisco</creatorcontrib><creatorcontrib>Pecho, Oscar E.</creatorcontrib><creatorcontrib>Morales, Juan Carlos</creatorcontrib><creatorcontrib>Paravina, Rade D.</creatorcontrib><creatorcontrib>Della Bona, Alvaro</creatorcontrib><creatorcontrib>Ghinea, Razvan</creatorcontrib><creatorcontrib>Pulgar, Rosa</creatorcontrib><creatorcontrib>Pérez, María del Mar</creatorcontrib><creatorcontrib>Herrera, Luis Javier</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of esthetic and restorative dentistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Carrillo‐Perez, Francisco</au><au>Pecho, Oscar E.</au><au>Morales, Juan Carlos</au><au>Paravina, Rade D.</au><au>Della Bona, Alvaro</au><au>Ghinea, Razvan</au><au>Pulgar, Rosa</au><au>Pérez, María del Mar</au><au>Herrera, Luis Javier</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Applications of artificial intelligence in dentistry: A comprehensive review</atitle><jtitle>Journal of esthetic and restorative dentistry</jtitle><addtitle>J Esthet Restor Dent</addtitle><date>2022-01</date><risdate>2022</risdate><volume>34</volume><issue>1</issue><spage>259</spage><epage>280</epage><pages>259-280</pages><issn>1496-4155</issn><eissn>1708-8240</eissn><abstract>Objective
To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research.
Materials and methods
The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years.
Results
Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling.
Conclusions
The insight provided by the present work has reported outstanding results in the design of high‐performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations.
Clinical significance
The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>34842324</pmid><doi>10.1111/jerd.12844</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0003-0974-4092</orcidid><orcidid>https://orcid.org/0000-0002-8459-5528</orcidid><orcidid>https://orcid.org/0000-0002-8312-7503</orcidid><orcidid>https://orcid.org/0000-0001-8865-2430</orcidid><orcidid>https://orcid.org/0000-0001-7314-5049</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
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| ispartof | Journal of esthetic and restorative dentistry, 2022-01, Vol.34 (1), p.259-280 |
| issn | 1496-4155 1708-8240 |
| language | eng |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Artificial Intelligence Color Deep learning Dentistry Forecasting Fuzzy logic Humans Image processing Learning algorithms Machine Learning Segmentation |
| title | Applications of artificial intelligence in dentistry: A comprehensive review |
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