Artificial intelligence in endodontics: Data preparation, clinical applications, ethical considerations, limitations, and future directions
Artificial intelligence (AI) is emerging as a transformative technology in healthcare, including endodontics. A gap in knowledge exists in understanding AI's applications and limitations among endodontic experts. This comprehensive review aims to (A) elaborate on technical and ethical aspects o...
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Veröffentlicht in: | International endodontic journal 2024-11, Vol.57 (11), p.1566-1595 |
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creator | Mohammad‐Rahimi, Hossein Sohrabniya, Fatemeh Ourang, Seyed AmirHossein Dianat, Omid Aminoshariae, Anita Nagendrababu, Venkateshbabu Dummer, Paul Michael Howell Duncan, Henry F. Nosrat, Ali |
description | Artificial intelligence (AI) is emerging as a transformative technology in healthcare, including endodontics. A gap in knowledge exists in understanding AI's applications and limitations among endodontic experts. This comprehensive review aims to (A) elaborate on technical and ethical aspects of using data to implement AI models in endodontics; (B) elaborate on evaluation metrics; (C) review the current applications of AI in endodontics; and (D) review the limitations and barriers to real‐world implementation of AI in the field of endodontics and its future potentials/directions. The article shows that AI techniques have been applied in endodontics for critical tasks such as detection of radiolucent lesions, analysis of root canal morphology, prediction of treatment outcome and post‐operative pain and more. Deep learning models like convolutional neural networks demonstrate high accuracy in these applications. However, challenges remain regarding model interpretability, generalizability, and adoption into clinical practice. When thoughtfully implemented, AI has great potential to aid with diagnostics, treatment planning, clinical interventions, and education in the field of endodontics. However, concerted efforts are still needed to address limitations and to facilitate integration into clinical workflows. |
doi_str_mv | 10.1111/iej.14128 |
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A gap in knowledge exists in understanding AI's applications and limitations among endodontic experts. This comprehensive review aims to (A) elaborate on technical and ethical aspects of using data to implement AI models in endodontics; (B) elaborate on evaluation metrics; (C) review the current applications of AI in endodontics; and (D) review the limitations and barriers to real‐world implementation of AI in the field of endodontics and its future potentials/directions. The article shows that AI techniques have been applied in endodontics for critical tasks such as detection of radiolucent lesions, analysis of root canal morphology, prediction of treatment outcome and post‐operative pain and more. Deep learning models like convolutional neural networks demonstrate high accuracy in these applications. However, challenges remain regarding model interpretability, generalizability, and adoption into clinical practice. When thoughtfully implemented, AI has great potential to aid with diagnostics, treatment planning, clinical interventions, and education in the field of endodontics. 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subjects | Artificial intelligence Artificial Intelligence - ethics clinical application data management Deep Learning Endodontics Endodontics - ethics Endodontics - methods Ethics Humans model implementation Neural networks Reviews Root canals |
title | Artificial intelligence in endodontics: Data preparation, clinical applications, ethical considerations, limitations, and future directions |
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