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2022 4
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Page 1
Deep learning for caries detection: A systematic review.
Mohammad-Rahimi H, Motamedian SR, Rohban MH, Krois J, Uribe SE, Mahmoudinia E, Rokhshad R, Nadimi M, Schwendicke F. Mohammad-Rahimi H, et al. Among authors: uribe se. J Dent. 2022 Jul;122:104115. doi: 10.1016/j.jdent.2022.104115. Epub 2022 Mar 30. J Dent. 2022. PMID: 35367318
OBJECTIVES: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection. ...CLINICAL SIGNIFICANC …
OBJECTIVES: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase …
Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning.
Feher B, Kuchler U, Schwendicke F, Schneider L, Cejudo Grano de Oro JE, Xi T, Vinayahalingam S, Hsu TH, Brinz J, Chaurasia A, Dhingra K, Gaudin RA, Mohammad-Rahimi H, Pereira N, Perez-Pastor F, Tryfonos O, Uribe SE, Hanisch M, Krois J. Feher B, et al. Among authors: uribe se. Diagnostics (Basel). 2022 Aug 14;12(8):1968. doi: 10.3390/diagnostics12081968. Diagnostics (Basel). 2022. PMID: 36010318 Free PMC article.
The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical artificial intelligence research. The human clinical diagnostic reasoning process uses contextual information, including the spa …
The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical …
Artificial intelligence for oral and dental healthcare: Core education curriculum.
Schwendicke F, Chaurasia A, Wiegand T, Uribe SE, Fontana M, Akota I, Tryfonos O, Krois J; IADR e-oral health network and the ITU/WHO focus group AI for health. Schwendicke F, et al. Among authors: uribe se. J Dent. 2023 Jan;128:104363. doi: 10.1016/j.jdent.2022.104363. Epub 2022 Nov 21. J Dent. 2023. PMID: 36410581
OBJECTIVES: Artificial intelligence (AI) is swiftly entering oral health services and dentistry, while most providers show limited knowledge and skills to appraise dental AI applications. ...The resulting curriculum was consented using an online Delphi process. RESU …
OBJECTIVES: Artificial intelligence (AI) is swiftly entering oral health services and dentistry, while most providers show lim …
Advanced Imaging in Dental Research: From Gene Mapping to AI Global Data.
Graves DT, Uribe SE. Graves DT, et al. Among authors: uribe se. J Dent Res. 2024 Dec;103(13):1329-1330. doi: 10.1177/00220345241293040. Epub 2024 Oct 27. J Dent Res. 2024. PMID: 39462808 Free PMC article.
Advances in imaging technologies combined with artificial intelligence (AI) are transforming dental, oral, and craniofacial research. This editorial highlights breakthroughs ranging from gene expression mapping to visualizing the availability of global AI data, prov …
Advances in imaging technologies combined with artificial intelligence (AI) are transforming dental, oral, and craniofacial re …
Artificial intelligence chatbots and large language models in dental education: Worldwide survey of educators.
Uribe SE, Maldupa I, Kavadella A, El Tantawi M, Chaurasia A, Fontana M, Marino R, Innes N, Schwendicke F. Uribe SE, et al. Eur J Dent Educ. 2024 Nov;28(4):865-876. doi: 10.1111/eje.13009. Epub 2024 Apr 8. Eur J Dent Educ. 2024. PMID: 38586899
INTRODUCTION: Interest is growing in the potential of artificial intelligence (AI) chatbots and large language models like OpenAI's ChatGPT and Google's Gemini, particularly in dental education. ...
INTRODUCTION: Interest is growing in the potential of artificial intelligence (AI) chatbots and large language models like Ope …
Core outcomes measures in dental computer vision studies (DentalCOMS).
Büttner M, Rokhshad R, Brinz J, Issa J, Chaurasia A, Uribe SE, Karteva T, Chala S, Tichy A, Schwendicke F. Büttner M, et al. Among authors: uribe se. J Dent. 2024 Nov;150:105318. doi: 10.1016/j.jdent.2024.105318. Epub 2024 Aug 27. J Dent. 2024. PMID: 39182639 Free article.
Publicly Available Dental Image Datasets for Artificial Intelligence.
Uribe SE, Issa J, Sohrabniya F, Denny A, Kim NN, Dayo AF, Chaurasia A, Sofi-Mahmudi A, Büttner M, Schwendicke F. Uribe SE, et al. J Dent Res. 2024 Dec;103(13):1365-1374. doi: 10.1177/00220345241272052. Epub 2024 Oct 18. J Dent Res. 2024. PMID: 39422586 Free PMC article.
The development of artificial intelligence (AI) in dentistry requires large and well-annotated datasets. However, the availability of public dental imaging datasets remains unclear. ...
The development of artificial intelligence (AI) in dentistry requires large and well-annotated datasets. However, the availabi …
Evaluating dental AI research papers: Key considerations for editors and reviewers.
Uribe SE, Hamdan MH, Valente NA, Yamaguchi S, Umer F, Tichy A, Pauwels R, Schwendicke F. Uribe SE, et al. J Dent. 2025 Sep;160:105867. doi: 10.1016/j.jdent.2025.105867. Epub 2025 May 30. J Dent. 2025. PMID: 40451605 Free article.
OBJECTIVE: Artificial intelligence (AI) is increasingly used in dental research for diagnosis, treatment planning, and disease prediction. ...
OBJECTIVE: Artificial intelligence (AI) is increasingly used in dental research for diagnosis, treatment planning, and disease …
Federated vs Local vs Central Deep Learning of Tooth Segmentation on Panoramic Radiographs.
Schneider L, Rischke R, Krois J, Krasowski A, Büttner M, Mohammad-Rahimi H, Chaurasia A, Pereira NS, Lee JH, Uribe SE, Shahab S, Koca-Ünsal RB, Ünsal G, Martinez-Beneyto Y, Brinz J, Tryfonos O, Schwendicke F. Schneider L, et al. Among authors: uribe se. J Dent. 2023 Aug;135:104556. doi: 10.1016/j.jdent.2023.104556. Epub 2023 May 18. J Dent. 2023. PMID: 37209769
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple data sources without directly sharing data. ...METHODS: We employed a dataset of 4,177 panoramic radiographs collected from nine different c …
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple …
The influence of a deep learning tool on the performance of oral and maxillofacial radiologists in the detection of apical radiolucencies.
Hamdan MH, Uribe SE, Tuzova L, Tuzoff D, Badr Z, Mol A, Tyndall DA. Hamdan MH, et al. Among authors: uribe se. Dentomaxillofac Radiol. 2025 Feb 1;54(2):118-124. doi: 10.1093/dmfr/twae054. Dentomaxillofac Radiol. 2025. PMID: 39656660
OBJECTIVES: This study aimed to assess the impact of a deep learning model on oral radiologists' ability to detect periapical radiolucencies on periapical radiographs. ...METHODS: This study used an annotated dataset and a beta version of a deep learning …
OBJECTIVES: This study aimed to assess the impact of a deep learning model on oral radiologists' ability to detect periapical …
15 results