https://www.um.edu.mt/library/oar/handle/123456789/426 2026-04-17T15:05:49Z 2026-04-17T15:05:49Z Dawa, Hossam Aroso, Carlos Vinhas, Ana Sofia Cortes, Arthur R. G. https://www.um.edu.mt/library/oar/handle/123456789/145595 2026-04-15T05:36:39Z 2026-01-01T00:00:00Z

Title: Artificial intelligence architectures in oral rehabilitation : a focused review of deep learning models for implant planning, prosthodontic design, and peri-implant diagnosis Authors: Dawa, Hossam; Aroso, Carlos; Vinhas, Ana Sofia; Cortes, Arthur R. G. Abstract: Deep learning is increasingly integrated into oral rehabilitation workflows, particularly in implant planning, prosthodontic design automation, and peri-implant diagnosis. However, reported performance is heterogeneous and difficult to compare across tasks, modalities, and validation designs. The goal of this study was to critically analyze deep learning architecture families applied to oral rehabilitation and to provide task-driven selection guidance supported by an evidence table reporting dataset characteristics, validation strategy, and performance metrics. A focused narrative review was conducted using transparent, database-specific search criteria (final n = 10 included studies), emphasizing implant planning (cone–beam computed tomography [CBCT]-based segmentation), prosthodontic design (intraoral scan [IOS]/mesh inputs), and peri-implant diagnosis (periapical/panoramic radiographs). Evidence certainty for each clinical task was assessed using GRADE-informed ratings (High/Moderate/Low/Very Low). Extracted variables included clinical task, imaging modality, dataset size, architecture, validation strategy (in ternal vs. internal + external), split level, ground truth protocol, and performance metrics. Astructured computational and hardware feasibility analysis was conducted for each architecture family to support real-world deployment planning. Encoder–decoder networks (U-Net/nnU-Net) dominate CBCT segmentation for implant planning, while detection architectures (Faster R-CNN, YOLO) support implant localization and peri-implant assess ment on radiographs. Generative models (3D GANs, transformer-based point-to-mesh networks) enable crown design from three-dimensional scans. Hybrid CNN–Transformer architectures show promise for multimodal CBCT–IOS fusion, though direct evidence from the included studies remains limited to a single study. External validation remains uncommonyetessential given the risk of domain shift. In conclusion, architecture selection should be anchored to task geometry (2D vs. 3D), artifact burden, and required clinical output type. Reporting standards should prioritize dataset transparency, validation rigor, multi-center external testing, and uncertainty-aware outputs.

2026-01-01T00:00:00Z Cortes, Arthur R. G. Barbosa, Joana Gonçalves, Virgínia Henriques, Bruno Sarmento, Bruno Rodrigues, Célia Fortuna Souza, Júlio C. M. Tiritan, Maria Elizabeth Vieira Brito, Nuno Bezerra Cass, Quezia Dinis-Oliveira, Ricardo Jorge Warnakulasuriya, Saman Bolanos-Garcia, Victor M. Bousbaa, Hassan https://www.um.edu.mt/library/oar/handle/123456789/143664 2026-02-13T13:42:09Z 2026-01-01T00:00:00Z

Title: Progress and insights in health and biomedical research Authors: Cortes, Arthur R. G.; Barbosa, Joana; Gonçalves, Virgínia; Henriques, Bruno; Sarmento, Bruno; Rodrigues, Célia Fortuna; Souza, Júlio C. M.; Tiritan, Maria Elizabeth; Vieira Brito, Nuno; Bezerra Cass, Quezia; Dinis-Oliveira, Ricardo Jorge; Warnakulasuriya, Saman; Bolanos-Garcia, Victor M.; Bousbaa, Hassan Abstract: On behalf of the Editorial Team of Scientific Letters, we are pleased to announce the publication of the journal’s fourth issue. In 2025, Scientific Letters continued its mission of disseminating high-quality open-access research across the fields of biology and medicine. The two review articles and five original research papers published this year highlight both foundational biological mechanisms and pressing clinical and public health issues. João Carvalho et al. performed a systematic integrative review addressing different orthodontic approaches to the traction of impacted canines. Their work critically analyzed existing techniques, highlighting the advantages and limitations of surgical and orthodontic strategies, and emphasizing the importance of individualized treatment planning to optimize functional and esthetic outcomes. This review contributes valuable guidance for clinical decision-making in orthodontic practice.

2026-01-01T00:00:00Z DeVito-Moraes, André Guaraci Vardasca, Isabela Souza Peñarrocha-Diago, Miguel Cortes, Arthur R. G. https://www.um.edu.mt/library/oar/handle/123456789/143663 2026-02-13T13:29:03Z 2026-01-01T00:00:00Z

Title: Impact of different yttrium oxide concentrations and sintering protocols on the flexural strength and optical properties of monolithic zirconia Authors: DeVito-Moraes, André Guaraci; Vardasca, Isabela Souza; Peñarrocha-Diago, Miguel; Cortes, Arthur R. G. Abstract: This study investigates the mechanical and optical properties of monolithic zirconia used in dentistry, focusing on how different concentrations of yttrium oxide and varied sintering times affect the material. A critical trade-off in ceramics has been reported in the literature, in which increased crystalline content (like in zirconia) leads to higher mechanical strength but lower aesthetic translucency. However, detailed information on this trade-off process for different types of zirconia is lacking. A total of seven types of zirconia varying in yttria content (3 mol% to 5 mol%) were tested across four sintering protocols available in a laboratory zirconia sintering device: Slow (12 h), Standard (8 h), Fast (3.5 h), and Ultrafast (1.15 h). The primary findings indicate that while a higher yttria concentration correlates with lower flexural strength and high translucency, the sintering time generally did not compromise mechanical strength or color variation across most samples. Nevertheless, the Fast and Ultrafast protocols did significantly reduce the translucency of zirconia with a high concentration of yttrium oxide.

2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/139973 2025-10-10T12:53:58Z 2025-01-01T00:00:00Z

Title: COVID-19 : investigating the impact of face masks on Maltese adults’ behaviour and attitudes regarding oral health Abstract: As implemented by the Maltese government in the form of preventive measures to deter the transmission of the COVID-19 virus, in accordance to the guidelines published by the WHO (World Health Organization, 2020), the use of face masks became an integral part of pandemic times, to the extent of being mandated. Considering the duration with which such masks were donned, this study explores the hypothesis of face mask use affecting the oral health of the minority of adults living in Malta including ‘mask mouth’ symptoms, dental-service seeking behaviour and oral hygiene habits using the specified research question below. A cross-sectional qualitative online survey was conducted and 419 respondents recruited, with statistical analysis demonstrating the mask wearing behaviour of Maltese adults, the significant relationships between mask wearing and oral health & general health while outlining smokers as high risk for ‘mask mouth’. Implications of this study include improving preventive advice during public health crises such as pandemics and to improve awareness of mask mouth in health care settings. Population – adults residing in Malta Intervention – the daily use of face masks related to the COVID-19 pandemic Comparison – (not present) Outcome – affect behaviour and attitudes towards oral health Description: M.D.S.(Melit.)

2025-01-01T00:00:00Z