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Retinal illnesses such as age-related macular degeneration (AMD) and diabetic maculopathy pose serious risks to vision in the developed world. The diagnosis and assessment of these disorders have undergone revolutionary change with the development of optical coherence tomography (OCT). This study proposes a novel method for improving clinical precision in retinal disease diagnosis by utilizing the strength of Attention-Based DenseNet, a deep learning architecture with attention processes. For model building and evaluation, a dataset of 84495 high-resolution OCT images divided into NORMAL, CNV, DME, and DRUSEN classes was used. Data augmentation techniques were employed to enhance the model's robustness. The Attention-Based DenseNet model achieved a validation accuracy of 0.9167 with a batch size of 32 and 50 training epochs. This discovery presents a promising route for more precise and speedy identification of retinal illnesses, ultimately enhancing patient care and outcomes in clinical settings by integrating cutting-edge technology with powerful neural network architectures. [ABSTRACT FROM AUTHOR]

Background: Additive manufacturing (three-dimensional (3D) printing) has become a leading manufacturing technique in dentistry due to its various advantages. However, its potential applications for dental ceramics are still being explored. Zirconia, among ceramics, has increasing popularity and applications in dentistry mostly due to its excellent properties. Although subtractive manufacturing (3D milling) is considered the most advanced technology for the fabrication of zirconia restorations, certain disadvantages are associated with it. Methods: A systematic review was piloted to compare the clinical performance of zirconium crowns that were fabricated using three-dimensional (3D) milling and 3D printing. A meta-analysis was performed, and studies published up to November 2022 were identified. The terms searched were "Zirconium crowns", "3D printing", "CAD/CAM" (Computer-Aided Design and Computer-Aided Manufacturing), "Milling", "dental crowns", and "3D milling". The characteristics that were compared were the year in which the study was published, study design, age of the patient, country, the number of crowns, the type of crown fabrication, marginal integrity, caries status, and outcomes. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to structure this systematic review. Out of eleven hundred and fifty titles identified after a primary search, nine articles were included in the quantitative analysis. The research question based on PICO/PECO (Participant, Intervention/exposure, Comparison, and Outcome) was "Do 3D-printed and milled (P) zirconia crowns and FDPs (I) have a better survival rate (O) when conventional prosthesis is also an option (C)"? The data collected were tabulated and compared, and the risk of bias and meta-analysis were later performed. Only nine articles (clinical research) were selected for the study. Since there were no clinical studies on the 3D printing of zirconium crowns, six in vitro studies were considered for the comparison. Zirconium crowns in the milling group had an average minimum follow-up of 6 months. Results: A moderate risk of bias was found, and survival was significant. A high heterogeneity level was noted among the studies. Marginal integrity, periodontal status, and survival rate were high. Linear regression depicted no statistical correlation between the type of cement used and the survival rate. Conclusions: It can be concluded that the milled crowns had a higher performance and satisfactory clinical survival. [ABSTRACT FROM AUTHOR]

Purpose: To compare the trueness and precision of 3D-printed versus milled monolithic zirconia crowns (MZCs)., Methods: A model of a maxilla with a prepared premolar was scanned with an industrial scanner (ATOSQ®, Gom) and an MZC was designed in computer-assisted-design (CAD) software (DentalCad®, Exocad). From that standard tessellation language (STL) file, 10 MZCs (test) were 3D-printed with a Lithography-based Ceramic Manufacturing (LCM) printer (CerafabS65®, Lithoz) and 10 MZCs (control) were milled using a 5-axis machine (DWX-52D®, DGShape). All MZCs were sintered and scanned with the aforementioned scanner. The surface data of each sample (overall crown, marginal area, occlusal surface) were superimposed to the original CAD file (ControlX®, Geomagic) to evaluate trueness: (90-10)/2, absolute average (ABS AVG) and root mean square (RMS) values were obtained for test and control groups (MathLab®, Mathworks) and used for analysis. Finally, the clinical precision (marginal adaptation, interproximal contacts) of test and control MZCs was investigated on a split-cast model printed (Solflex350®, Voco) from the CAD project, and compared., Results: The milled MZCs had a significantly higher trueness than the 3D-printed ones, overall [(90-10)/2 printed 37.8 µm vs milled 21.2 µm; ABS AVG printed 27.2 µm vs milled 15.1 µm; RMS printed 33.2 µm vs milled 20.5 µm; p = 0.000005], at the margins [(90-10)/2 printed 25.6 µm vs milled 12.4 µm; ABS AVG printed 17.8 µm vs milled 9.4 µm; RMS printed 22.8 µm vs milled 15.6 µm; p= 0.000011] and at the occlusal level [(90-10)/2 printed 50.4 µm vs milled 21.9 µm; ABS AVG printed 29.6 µm vs milled 14.7 µm; RMS printed 38.9 µm vs milled 22.5 µm; p = 0.000005]. However, with regard to precision, both test and control groups scored highly, with no significant difference either in the quality of interproximal contact points (p = 0.355) or marginal closure (p = 0.355)., Conclusions: Milled MZCs had a statistically higher trueness than 3D-printed ones; all crowns, however, showed high precision, compatible with the clinical use., Clinical Significance: Although milled MZCs remain more accurate than 3D-printed ones, the LCM technique seems able to guarantee the production of clinically precise zirconia crowns., (Copyright © 2021. Published by Elsevier Ltd.)