Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners
Artificial intelligence (AI) has gained significant traction in medical image analysis, including dentistry, aiding clinicians in making timely and accurate diagnoses. Radiographs, such as orthopantomograms (OPGs) and intraoral radiographs, along with clinical photographs, are the primary imaging mo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/12/1/9 |
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| author | Ruchika Raj Ravikumar Rajappa Vijayalakshmi Murthy Mahyar Osanlouy Daniel Lawrence Mahen Ganhewa Nicola Cirillo |
| author_facet | Ruchika Raj Ravikumar Rajappa Vijayalakshmi Murthy Mahyar Osanlouy Daniel Lawrence Mahen Ganhewa Nicola Cirillo |
| author_sort | Ruchika Raj |
| collection | DOAJ |
| description | Artificial intelligence (AI) has gained significant traction in medical image analysis, including dentistry, aiding clinicians in making timely and accurate diagnoses. Radiographs, such as orthopantomograms (OPGs) and intraoral radiographs, along with clinical photographs, are the primary imaging modalities employed for AI-powered analysis in the dental field. In this review, we discuss the most recent research and product developments concerning the clinical application of AI as a visual aid in dentistry and introduce the concept of Observational Diagnostics (ODs) as a structured method to standardise image analysis. ODs serve as foundational elements for AI-driven diagnostic aids and have the potential to improve the consistency and reliability of diagnostic data used in treatment planning. We provide illustrative examples to demonstrate how ODs not only represent a significant advancement towards more precise diagnostic aids but also provide the basis for the generation of evidence-based treatment recommendations. These OD-based algorithms have been integrated into chairside AI applications to streamline clinical workflows to improve consistency, accuracy, and efficiency. |
| format | Article |
| id | doaj-art-9a4a7046474748ddac48b5670bc677f6 |
| institution | Kabale University |
| issn | 2306-5354 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj-art-9a4a7046474748ddac48b5670bc677f62025-01-24T13:22:56ZengMDPI AGBioengineering2306-53542024-12-01121910.3390/bioengineering12010009Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental PractitionersRuchika Raj0Ravikumar Rajappa1Vijayalakshmi Murthy2Mahyar Osanlouy3Daniel Lawrence4Mahen Ganhewa5Nicola Cirillo6CoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaCoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaCoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaCoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaCoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaCoTreat, CoTreat Pty Ltd., Melbourne, VIC 3000, AustraliaFaculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, 720, Swanston Street, Carlton, VIC 3053, AustraliaArtificial intelligence (AI) has gained significant traction in medical image analysis, including dentistry, aiding clinicians in making timely and accurate diagnoses. Radiographs, such as orthopantomograms (OPGs) and intraoral radiographs, along with clinical photographs, are the primary imaging modalities employed for AI-powered analysis in the dental field. In this review, we discuss the most recent research and product developments concerning the clinical application of AI as a visual aid in dentistry and introduce the concept of Observational Diagnostics (ODs) as a structured method to standardise image analysis. ODs serve as foundational elements for AI-driven diagnostic aids and have the potential to improve the consistency and reliability of diagnostic data used in treatment planning. We provide illustrative examples to demonstrate how ODs not only represent a significant advancement towards more precise diagnostic aids but also provide the basis for the generation of evidence-based treatment recommendations. These OD-based algorithms have been integrated into chairside AI applications to streamline clinical workflows to improve consistency, accuracy, and efficiency.https://www.mdpi.com/2306-5354/12/1/9artificial intelligenceobservational diagnosticsOD-based algorithmsevidence-based treatmentdentistryAI applications |
| spellingShingle | Ruchika Raj Ravikumar Rajappa Vijayalakshmi Murthy Mahyar Osanlouy Daniel Lawrence Mahen Ganhewa Nicola Cirillo Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners Bioengineering artificial intelligence observational diagnostics OD-based algorithms evidence-based treatment dentistry AI applications |
| title | Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners |
| title_full | Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners |
| title_fullStr | Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners |
| title_full_unstemmed | Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners |
| title_short | Observational Diagnostics: The Building Block of AI-Powered Visual Aid for Dental Practitioners |
| title_sort | observational diagnostics the building block of ai powered visual aid for dental practitioners |
| topic | artificial intelligence observational diagnostics OD-based algorithms evidence-based treatment dentistry AI applications |
| url | https://www.mdpi.com/2306-5354/12/1/9 |
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