Publication
Interdisciplinary applications of artificial intelligence (AI) in dentistry : a focus on endodontics, oral pathology, prosthodontics, orthodontics and periodontics
| dc.contributor.advisor | Santos, Ana Teresa | |
| dc.contributor.author | Allani, Hela | |
| dc.date.accessioned | 2024-09-30T11:04:15Z | |
| dc.date.available | 2024-09-30T11:04:15Z | |
| dc.date.issued | 2024-08-01 | |
| dc.description | Dissertação para obtenção do grau de Mestre no Instituto Universitário Egas Moniz | pt_PT |
| dc.description.abstract | This thesis explores the revolutionary impact of Artificial Intelligence (AI) in dentistry, reflecting on its potential to reshape traditional practices and meet the increasing demands for high-quality dental care. The aim of this research is to examine how AI has evolved in dentistry over the past two decades, driven by two pivotal questions: "What are the current emerging trends and developments in AI in dentistry?" and "What implications do these trends have for the future of AI in the dental field?". Utilizing the Scopus database, a comprehensive bibliometric analysis of literature from 2000 to 2023 was conducted to address these inquiries. The findings reveal a significant increase in AI-related publications, especially between 2018 and 2023, underscoring a rapid expansion in AI applications that enhance diagnostic precision and treatment planning. Techniques such as deep learning and neural networks have transformed dental practices by enhancing diagnostic precision and reducing workload. AI technologies, particularly CNNs and ANNs, have improved the accuracy of radiographic analysis, from detecting dental pathologies to automating cephalometric evaluations, thereby optimizing treatment outcomes. This advocacy is underpinned by the need for AI applications in dentistry to be both efficacious and ethically sound, ensuring that they not only improve clinical outcomes but also adhere to the highest standards of patient care. | pt_PT |
| dc.description.abstract | This thesis explores the revolutionary impact of Artificial Intelligence (AI) in dentistry, reflecting on its potential to reshape traditional practices and meet the increasing demands for high-quality dental care. The aim of this research is to examine how AI has evolved in dentistry over the past two decades, driven by two pivotal questions: "What are the current emerging trends and developments in AI in dentistry?" and "What implications do these trends have for the future of AI in the dental field?". Utilizing the Scopus database, a comprehensive bibliometric analysis of literature from 2000 to 2023 was conducted to address these inquiries. The findings reveal a significant increase in AI-related publications, especially between 2018 and 2023, underscoring a rapid expansion in AI applications that enhance diagnostic precision and treatment planning. Techniques such as deep learning and neural networks have transformed dental practices by enhancing diagnostic precision and reducing workload. AI technologies, particularly CNNs and ANNs, have improved the accuracy of radiographic analysis, from detecting dental pathologies to automating cephalometric evaluations, thereby optimizing treatment outcomes. This advocacy is underpinned by the need for AI applications in dentistry to be both efficacious and ethically sound, ensuring that they not only improve clinical outcomes but also adhere to the highest standards of patient care. | pt_PT |
| dc.identifier.tid | 203697057 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.26/52300 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Artificial intelligence | pt_PT |
| dc.subject | Dentistry | pt_PT |
| dc.subject | Treatment planning | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.title | Interdisciplinary applications of artificial intelligence (AI) in dentistry : a focus on endodontics, oral pathology, prosthodontics, orthodontics and periodontics | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado Integrado em Medicina Dentária | pt_PT |