The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review
Abstract Background Generative AI technologies offer significant opportunities to enhance orthodontic education by improving knowledge retention, clinical decision-making, and skills training. This systematic review aimed to evaluate the impact of generative AI tools in orthodontic education, focusi...
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BMC
2025-06-01
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| Series: | BMC Oral Health |
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| Online Access: | https://doi.org/10.1186/s12903-025-06070-7 |
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| author | Martin Baxmann Krisztina Kárpáti Zoltán Baráth |
| author_facet | Martin Baxmann Krisztina Kárpáti Zoltán Baráth |
| author_sort | Martin Baxmann |
| collection | DOAJ |
| description | Abstract Background Generative AI technologies offer significant opportunities to enhance orthodontic education by improving knowledge retention, clinical decision-making, and skills training. This systematic review aimed to evaluate the impact of generative AI tools in orthodontic education, focusing on knowledge retention, decision-making, and practical skills. Methods A comprehensive literature search was conducted across PubMed, Cochrane Library, ERIC, CINAHL, and IEEE Xplore from January 2010 to December 2023. Studies evaluating the integration of generative AI in dental and orthodontic education were included. Seventeen studies met the inclusion criteria. Risk of bias was assessed using the Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale, with the GRADE approach used to evaluate evidence quality. Results Generative AI improved knowledge retention and clinical decision-making through adaptive learning pathways and real-time feedback. Barriers included limited faculty training, technical infrastructure deficits, and educator resistance. Conclusions Generative AI holds transformative potential for orthodontic education but requires addressing practical and ethical challenges. Future research should focus on longitudinal studies to validate long-term impact and explore integration strategies. |
| format | Article |
| id | doaj-art-8f650a875eb04a73b9f4d31d9b7a8d9e |
| institution | DOAJ |
| issn | 1472-6831 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Oral Health |
| spelling | doaj-art-8f650a875eb04a73b9f4d31d9b7a8d9e2025-08-20T03:06:41ZengBMCBMC Oral Health1472-68312025-06-0125111010.1186/s12903-025-06070-7The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic reviewMartin Baxmann0Krisztina Kárpáti1Zoltán Baráth2Department of Orthodontics, Faculty of Education and Research, DTMD UniversityDepartment of Orthodontics and Pediatric Dentistry, Faculty of Dentistry, University of SzegedDepartment of Prosthodontics, Faculty of Dentistry, University of SzegedAbstract Background Generative AI technologies offer significant opportunities to enhance orthodontic education by improving knowledge retention, clinical decision-making, and skills training. This systematic review aimed to evaluate the impact of generative AI tools in orthodontic education, focusing on knowledge retention, decision-making, and practical skills. Methods A comprehensive literature search was conducted across PubMed, Cochrane Library, ERIC, CINAHL, and IEEE Xplore from January 2010 to December 2023. Studies evaluating the integration of generative AI in dental and orthodontic education were included. Seventeen studies met the inclusion criteria. Risk of bias was assessed using the Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale, with the GRADE approach used to evaluate evidence quality. Results Generative AI improved knowledge retention and clinical decision-making through adaptive learning pathways and real-time feedback. Barriers included limited faculty training, technical infrastructure deficits, and educator resistance. Conclusions Generative AI holds transformative potential for orthodontic education but requires addressing practical and ethical challenges. Future research should focus on longitudinal studies to validate long-term impact and explore integration strategies.https://doi.org/10.1186/s12903-025-06070-7Artificial intelligenceMachine learningDental educationOrthodonticsClinical decision-makingEducational technology |
| spellingShingle | Martin Baxmann Krisztina Kárpáti Zoltán Baráth The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review BMC Oral Health Artificial intelligence Machine learning Dental education Orthodontics Clinical decision-making Educational technology |
| title | The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review |
| title_full | The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review |
| title_fullStr | The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review |
| title_full_unstemmed | The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review |
| title_short | The potentials and challenges of integrating generative artificial intelligence (AI) in dental and orthodontic education: a systematic review |
| title_sort | potentials and challenges of integrating generative artificial intelligence ai in dental and orthodontic education a systematic review |
| topic | Artificial intelligence Machine learning Dental education Orthodontics Clinical decision-making Educational technology |
| url | https://doi.org/10.1186/s12903-025-06070-7 |
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