J Prosthet Dent
Professor, State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, PR China. Electronic address:
Published: January 2024
This clinical report describes a digital workflow for the rehabilitation of an 8-year-old patient diagnosed with ectodermal dysplasia. Based on the patient's digital primary casts, small custom trays and an arch tracer were designed and 3-dimensionally printed. The mandibular custom tray and retention plate with a tracing screw were assembled with tracing plate, forming an individual assembled mini-arch tracer system to record the jaw relationship together with a conventional facebow and a digital articulator. In addition, composite resin injection guides were designed and fabricated to form the predesigned targeted shape of the abutment teeth and provide a buffer. By following this workflow, complete overdentures with good fit, occlusion, and acceptable esthetics were delivered.
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http://dx.doi.org/10.1016/j.prosdent.2023.11.036 | DOI Listing |
Bioinform Biol Insights
March 2025
Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Jena, Germany.
The importance of genomic surveillance strategies for pathogens has been particularly evident during the coronavirus disease 2019 (COVID-19) pandemic, as genomic data from the causative agent, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), have guided public health decisions worldwide. Bayesian phylodynamic inference, integrating epidemiology and evolutionary biology, has become an essential tool in genomic epidemiological surveillance. It enables the estimation of epidemiological parameters, such as the reproductive number, from pathogen sequence data alone.
View Article and Find Full Text PDFHealthcare (Basel)
February 2025
Department of Health Informatics, College of Applied Medical Sciences, Qassim University, Buraydah 52571, Saudi Arabia.
Background: Mobile health (mHealth) applications have transformed healthcare delivery by enhancing accessibility, patient monitoring, and clinician communication. Despite these advantages, significant barriers hinder their adoption among healthcare practitioners, limiting their effectiveness in primary care settings. Understanding these barriers is crucial for optimizing mHealth integration into healthcare systems.
View Article and Find Full Text PDFCancers (Basel)
February 2025
Department of Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany.
Background: The increase in multiparametric magnetic resonance imaging (mpMRI) examinations as a fundamental tool in prostate cancer (PCa) diagnostics raises the need for supportive computer-aided imaging analysis. Therefore, we evaluated the performance of a commercially available AI-based algorithm for prostate cancer detection and classification in a multi-center setting.
Methods: Representative patients with 3T mpMRI between 2017 and 2022 at three different university hospitals were selected.
Int J Comput Assist Radiol Surg
March 2025
Department of Computer Science, UCL Hawkes Institute, University College London, London, UK.
Purpose: Colorectal cancer is one of the most prevalent cancers worldwide, highlighting the critical need for early and accurate diagnosis to reduce patient risks. Inaccurate diagnoses not only compromise patient outcomes but also lead to increased costs and additional time burdens for clinicians. Enhancing diagnostic accuracy is essential, and this study focuses on improving the accuracy of polyp classification using the NICE classification, which evaluates three key features: colour, vessels, and surface pattern.
View Article and Find Full Text PDFSLAS Technol
March 2025
Sygnature Discovery Ltd., BioCity, Pennyfoot Street, Nottingham, United Kingdom.
Drug discovery is a collaborative endeavor that often involves scientists from various disciplines and global collaborators. Efficient real-time sharing and updating of design-make-test-analyze (DMTA) information remains a challenge in drug discovery, hindering timely decision-making and project advancement. We propose a novel approach utilizing existing electronic inventory systems as DMTA workflow tracking platforms.
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