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| http://dx.doi.org/10.1136/bmj.302.6774.472-d | DOI Listing |
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Bayesian network for predicting mandibular third molar extraction difficulty.
BMC Oral Health
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Sub-Institute of Public Safety Standardization, China National Institute of Standardization, No.4 Zhichun Road, Haidian District, Beijing, 100191, PR China.
Background: This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient's personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications.
Methods: Relevant articles were searched to identify risk factors. Clinical knowledge and experience were used to analyse the risk factors to establish the Bayesian network.
Accuracy of Full-Arch Intraoral Scans Versus Conventional Impression: A Systematic Review with a Meta-Analysis and a Proposal to Standardise the Analysis of the Accuracy.
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Dental Unit, Department of Surgical Sciences (DISC), University of Genoa, 16132 Genova, Italy.
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G. Nadjakov Institute of Solid-State Physics, Bulgarian Academy of Sciences, 72 Tzarigradsko Chaussee, 1784 Sofia, Bulgaria.
: Orthodontic archwires undergo chemical and structural changes in the complex intraoral environment. The present work aims to investigate the safe duration for intraoral use (related to the nickel release hypothesis) of different types of nickel-containing wires. By analyzing how the nickel content (NC) varies over time, we aim to provide practical recommendations for the optimal use of said archwires.
View Article and Find Full Text PDFNURBS curve shape prior-guided multiscale attention network for automatic segmentation of the inferior alveolar nerve.
Comput Med Imaging Graph
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Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address:
Accurate segmentation of the inferior alveolar nerve (IAN) within Cone-Beam Computed Tomography (CBCT) images is critical for the precise planning of oral and maxillofacial surgeries, especially to avoid IAN damage. Existing methods often fail due to the low contrast of the IAN and the presence of artifacts, which can cause segmentation discontinuities. To address these challenges, this paper proposes a novel approach that employs Non-Uniform Rational B-Spline (NURBS) curve shape priors into a multiscale attention network for the automatic segmentation of the IAN.
View Article and Find Full Text PDFMicroplastic pollution in the marine environment: Distribution factors and mitigation strategies in different oceans.
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Department of Civil and Environmental Engineering, Seoul National University, 151-744 Seoul, South Korea.
As the COVID-19 pandemic began in 2020, plastic usage spiked, and microplastic (MP) generation has increased dramatically. It is documented that MP can transfer from the source to the ocean environment where they accumulate as the destination. Therefore, it is essential to understand their transferring pathways and effective environmental factors to determine the distribution of MPs in the marine environment.
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