A review of deep learning in dentistry

Neurocomputing, Journal Year: 2023, Volume and Issue: 554, P. 126629 - 126629

Published: July 27, 2023

Oral diseases have a significant impact on human health, often going unnoticed in their early stages. Deep learning, promising field artificial intelligence, has shown remarkable success various domains, especially dentistry. This paper aims to provide an overview of recent research deep learning applications dentistry, with focus dental imaging. algorithms perform well difficult tasks such as image segmentation and recognition, enabling accurate identification oral conditions abnormalities. Integration other health data offers holistic understanding the relationship between systemic health. However, there are still many challenges that need be addressed.

Language: Английский

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Role of Artificial Intelligence (AI) in Patient Education and Communication in Dentistry

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: May 7, 2024

Effective patient education and communication are integral components of quality dental care, contributing to informed decision-making, treatment compliance, positive clinical outcomes. However, traditional methods face challenges such as language barriers, anxiety, information retention issues. Artificial intelligence (AI) presents innovative solutions enhance engagement in dentistry. This review explores the transformative role AI redefining strategies, focusing on applications, benefits, challenges, future directions. A literature search identified articles from 2018 2024, encompassing empirical evidence conceptual frameworks related communication. Key findings reveal AI's potential offer personalized educational materials, virtual consultations, translation tools, reality simulations, improving understanding experience. Despite advancements, concerns about overreliance, accuracy, implementation costs, acceptance, privacy, regulatory compliance persist. Future implications suggest ability track progress, analyze feedback, streamline administrative processes, provide ongoing support, enhancing oral health ethical, regulatory, equity considerations require attention for responsible deployment widespread adoption. Overall, holds promise revolutionizing education, communication, care delivery, emphasizing need comprehensive strategies address emerging maximize benefits.

Language: Английский

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The flexural strength of 3D-printed provisional restorations fabricated with different resins: a systematic review and meta-analysis

BMC Oral Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: Jan. 10, 2024

Three-dimensional (3D) printing technology has revolutionized dentistry, particularly in fabricating provisional restorations. This systematic review and meta-analysis aimed to thoroughly evaluate the flexural strength of restorations produced using 3D while considering impact different resin materials.

Language: Английский

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Dental biomaterials redefined: molecular docking and dynamics-driven dental resin composite optimization

BMC Oral Health, Journal Year: 2024, Volume and Issue: 24(1)

Published: May 13, 2024

Abstract Background Dental resin-based composites are widely recognized for their aesthetic appeal and adhesive properties, which make them integral to modern restorative dentistry. Despite advantages, adhesion biomechanical performance challenges persist, necessitating innovative strategies improvement. This study addressed the associated with properties in dental by employing molecular docking dynamics simulation. Methods Molecular assesses binding energies provides valuable insights into interactions between monomers, fillers, coupling agents. investigation prioritizes SiO 2 TRIS, considering consistent influence. simulations, executed Forcite module COMPASS II force field, extend analysis mechanical of composite complexes. The simulations encompassed energy minimization, controlled NVT NPT ensemble equilibration stages. Notably, spanned a duration 50 ns. Results TRIS consistently emerged as influential components, showcasing versatility promoting solid interactions. A correlation matrix underscores significant roles van der Waals desolvation determining overall energy. provide in-depth HEMA-SiO -TRIS excelled stiffness, BisGMA-SiO prevailed terms flexural strength, EBPADMA-SiO offered balanced combination properties. Conclusion These findings optimizing tailored diverse clinical requirements. While demonstrates distinct strengths, this emphasizes need further research. Future investigations should validate computational experimentally assess material's response dynamic environmental factors.

Language: Английский

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The relationships of personality traits on perceptions and attitudes of dentistry students towards AI

BMC Medical Education, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 6, 2025

Artificial intelligence (AI) has gained significant attention in dentistry due to its potential revolutionize practice and improve patient outcomes. However, dentists' views attitudes toward technology can affect the application of AI. This perception attitude be affected by personality traits individuals. study aims evaluate perceptions students cross-sectional was conducted on dental at Ordu University Faculty Dentistry, involving a sample 83 students. The utilized Big Five 50 Test 5-point Likert scale gather data 20 statements regarding AI dentistry. Data were analyzed using IBM SPSS Statistics software, chi-square test employed assess relationship between their towards artificial intelligence, as well gender intelligence. Statistical significance set P < 0.05. involved participants, with 29 male 54 female participants. most common Openness Agreeableness, whereas least Extraversion. Participants found useful believed it could help dentists radiographs. agreed statement that they would trust more than dentist evaluating radiograph results. A statistically difference personal expressions comparing Males familiar females. vary based traits. Developing educational strategies tailored these foster positive integration into practice.

Language: Английский

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In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations

Journal of Materials Science Materials in Medicine, Journal Year: 2024, Volume and Issue: 35(1)

Published: June 4, 2024

Abstract Aim: This study aimed to comprehensively assess the biocompatibility and toxicity profiles of poly(methyl methacrylate) (PMMA) its monomeric unit, methyl methacrylate (MMA), crucial components in dental materials for interim prosthetic restorations. Methodology: Molecular docking was employed predict binding affinities, energetics, steric features MMA PMMA with selected receptors involved bone metabolism tissue development, including RANKL, Fibronectin, BMP9, NOTCH2, other related receptors. The HADDOCK standalone version utilized calculations, employing a Lamarckian genetic algorithm explore conformational space ligand-receptor interactions. Furthermore, molecular dynamics (MD) simulations over 100 nanoseconds were conducted using GROMACS package evaluate dynamic actions structural stability. LigandScout pharmacophore modeling, which employs shape-based screening approach identify potential ligand sites on protein targets. Results: studies elucidated promising interactions between key biomolecular targets relevant applications. MD simulation results provided strong evidence supporting stability complexes time. Pharmacophore modeling highlighted significance carbonyl hydroxyl groups as pharmacophoric features, indicating compounds favorable profiles. Conclusion: underscores applications, emphasizing stability, interactions, safety considerations. These findings lay foundation future advancements biomaterials, guiding design optimization enhanced biocompatibility. Future directions include experimental validation computational development PMMA-based improved clinical performance. Graphical

Language: Английский

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Artificial intelligence-powered dentistry: Probing the potential, challenges, and ethicality of artificial intelligence in dentistry

Digital Health, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

Introduction Healthcare amelioration is exponential to technological advancement. In the recent era of automation, consolidation artificial intelligence (AI) in dentistry has rendered transformation oral healthcare from a hardware-centric approach software-centric approach, leading enhanced efficiency and improved educational clinical outcomes. Objectives The aim this narrative overview extend succinct major events innovations that led creation modern-day AI applicability former dentistry. This article also prompts workers endeavor liable optimal for effective incorporation technology into their practice promote health by exploring potentials, constraints, ethical considerations Methods A comprehensive searching white grey literature was carried out collect assess data on AI, its use dentistry, associated challenges concerns. Results still evolving phase with paramount applicabilities relevant risk prediction, diagnosis, decision-making, prognosis, tailored treatment plans, patient management, academia as well concerns implementation. Conclusion upsurging advancements have resulted transformations promising outcomes across all domains futurity, may be capable executing multitude tasks domain healthcare, at level or surpassing ability mankind. However, could significant benefit only if it utilized under responsibility, ethicality universality.

Language: Английский

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Efficacy of different adhesive systems in bonding direct resin composite restorations: a systematic review and meta-analysis

Evidence-Based Dentistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

Language: Английский

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Exosomal Biomarkers for Prognosis in Oral Squamous Cell Carcinoma—A Systematic Review of Emerging Technologies

Journal of Craniofacial Surgery, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 26, 2025

Background: Oral squamous cell carcinoma (OSCC) is a significant health issue because of its aggressive nature and poor prognosis during the advanced stages. Exosomal biomarkers have emerged as promising entities for facilitating an enhanced existing assessment diagnosis in OSCC, particularly monitoring noninvasive behavior tumors. The authors tried to assess potential role these exosomal OSCC through this systematic review. Methods: Seven databases, PubMed, Scopus, Web Science, Embase, Cochrane Library, CINAHL, ProQuest, were searched systematically. Boolean operators, along with MeSH terms, utilized refining search strings retrieve appropriate studies. included studies focusing on derived from tissues or lines, emphasis their prognostic. Results: We 7 that probed miRNAs, lncRNAs, proteins exosomes. A few particular such miR-155, miR-21, miR-126, miR-130a showed correlation patients' outcomes progression OSCC. These miRNAs continuously association pathways having activities related promotion tumor growth, regulation immune system, angiogenesis. Interestingly, like Arginase-1 CKAP4 demonstrated significance metastasis via exosomes could be exploited risk metastasis. Another group lncRNAs screened contents has opened exciting possibility uncovering functions noncoding RNAs pathogenesis Conclusions: Our results conclude biomarkers, including proteins, great improve accuracy thus Some proven instrumental non-invasive diagnostics, whereas more informative concerning complicated mechanisms progression. above inconsistency molecular targets between indicates play complex future should focus combining different types further enhancement clinical applications management patients.

Language: Английский

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The Association Between Genetic Factors and Temporomandibular Disorders: A Systematic Literature Review

Archives of Oral Biology, Journal Year: 2024, Volume and Issue: 166, P. 106032 - 106032

Published: June 19, 2024

This study aimed to investigate the correlation between genetic factors and occurrence progression of temporomandibular disorders (TMDs) using a comprehensive review meta-analysis.

Language: Английский

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