Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives
Artificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodont...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Healthcare |
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| Online Access: | https://www.mdpi.com/2227-9032/10/11/2188 |
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| author | Anum Fatima Imran Shafi Hammad Afzal Isabel De La Torre Díez Del Rio-Solá M. Lourdes Jose Breñosa Julio César Martínez Espinosa Imran Ashraf |
| author_facet | Anum Fatima Imran Shafi Hammad Afzal Isabel De La Torre Díez Del Rio-Solá M. Lourdes Jose Breñosa Julio César Martínez Espinosa Imran Ashraf |
| author_sort | Anum Fatima |
| collection | DOAJ |
| description | Artificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology. This article aims to provide a systematic review of current clinical applications of artificial intelligence within different fields of dentistry. The preferred reporting items for systematic reviews (PRISMA) statement was used as a formal guideline for data collection. Data was obtained from research studies for 2009–2022. The analysis included a total of 55 papers from Google Scholar, IEEE, PubMed, and Scopus databases. Results show that artificial intelligence has the potential to improve dental care, disease diagnosis and prognosis, treatment planning, and risk assessment. Finally, this study highlights the limitations of the analyzed studies and provides future directions to improve dental care. |
| first_indexed | 2024-03-09T19:02:11Z |
| format | Article |
| id | doaj.art-06eff66da5b94640a272f7c7044748b8 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T19:02:11Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-06eff66da5b94640a272f7c7044748b82023-11-24T04:51:13ZengMDPI AGHealthcare2227-90322022-10-011011218810.3390/healthcare10112188Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future PerspectivesAnum Fatima0Imran Shafi1Hammad Afzal2Isabel De La Torre Díez3Del Rio-Solá M. Lourdes4Jose Breñosa5Julio César Martínez Espinosa6Imran Ashraf7National Centre for Robotics, National University of Sciences and Technology (NUST), Islamabad 44000, PakistanCollege of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad 44000, PakistanMilitary College of Signals (MCS), National University of Sciences and Technology (NUST), Islamabad 44000, PakistanDepartment of Signal Theory and Communications and Telematic Engineering, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, SpainDepartment of Vascular Surgery, University Hospital of Valladolid, Paseo de Belén 15, 47011 Valladolid, SpainUniversidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, SpainUniversidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, SpainDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, KoreaArtificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology. This article aims to provide a systematic review of current clinical applications of artificial intelligence within different fields of dentistry. The preferred reporting items for systematic reviews (PRISMA) statement was used as a formal guideline for data collection. Data was obtained from research studies for 2009–2022. The analysis included a total of 55 papers from Google Scholar, IEEE, PubMed, and Scopus databases. Results show that artificial intelligence has the potential to improve dental care, disease diagnosis and prognosis, treatment planning, and risk assessment. Finally, this study highlights the limitations of the analyzed studies and provides future directions to improve dental care.https://www.mdpi.com/2227-9032/10/11/2188dentistryartificial intelligencedeep learningclinical applications |
| spellingShingle | Anum Fatima Imran Shafi Hammad Afzal Isabel De La Torre Díez Del Rio-Solá M. Lourdes Jose Breñosa Julio César Martínez Espinosa Imran Ashraf Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives Healthcare dentistry artificial intelligence deep learning clinical applications |
| title | Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives |
| title_full | Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives |
| title_fullStr | Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives |
| title_full_unstemmed | Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives |
| title_short | Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives |
| title_sort | advancements in dentistry with artificial intelligence current clinical applications and future perspectives |
| topic | dentistry artificial intelligence deep learning clinical applications |
| url | https://www.mdpi.com/2227-9032/10/11/2188 |
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