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2021 1
2022 4
2023 2

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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 Review.
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. DATA: We selected diagn …
OBJECTIVES: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase …
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 …
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 …
Dental Research Data Availability and Quality According to the FAIR Principles.
Uribe SE, Sofi-Mahmudi A, Raittio E, Maldupa I, Vilne B. Uribe SE, et al. J Dent Res. 2022 Oct;101(11):1307-1313. doi: 10.1177/00220345221101321. Epub 2022 Jun 2. J Dent Res. 2022. PMID: 35656591 Free PMC article.
Our findings indicated that dental researchers rarely shared data, and when they did share, the FAIR quality was suboptimal. Machine learning algorithms could understand 1% of available dental research data. These undermine the reproducibility of dental research and …
Our findings indicated that dental researchers rarely shared data, and when they did share, the FAIR quality was suboptimal. Machine …
Artificial intelligence in dental research: Checklist for authors, reviewers, readers.
Schwendicke F, Singh T, Lee JH, Gaudin R, Chaurasia A, Wiegand T, Uribe S, Krois J; IADR e-oral health network and the ITU WHO focus group AI for Health. Schwendicke F, et al. Among authors: uribe s. J Dent. 2021 Apr;107:103610. doi: 10.1016/j.jdent.2021.103610. Epub 2021 Feb 22. J Dent. 2021. PMID: 33631303
OBJECTIVES: The number of studies employing artificial intelligence (AI), specifically machine and deep learning, is growing fast. ...METHODS: Lending from existing reviews, standards and other guidance documents, an initial draft of the checkli …
OBJECTIVES: The number of studies employing artificial intelligence (AI), specifically machine and deep learn …
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. ...CONCLUSION: If data pooling (for CL) is not feasible, FL is shown to be a useful alternative …
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple …