Advancements in Minimally Invasive Techniques in Pediatric Dentistry: A Review

Cureus, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 5, 2025

Minimally invasive dentistry (MID) has revolutionized pediatric dental care by emphasizing the preservation of healthy tooth structures, reducing treatment-related trauma, and improving patient compliance. This narrative review explores advancements in MID techniques, including silver diamine fluoride (SDF), resin infiltration, atraumatic restorative treatment (ART), bioactive materials, laser-assisted therapies, three-dimensional (3D) printing technologies. These approaches prioritize early diagnosis, prevention, conservative management, aligning with patient-centered sustainable practices. SDF demonstrates high efficacy arresting caries progression but presents esthetic challenges due to discoloration. Resin infiltration provides noninvasive for white spot lesions, while ART offers cost-effective child-friendly management resource-limited settings. Bioactive materials support tissue regeneration, laser technologies enable precise painless procedures, although their adoption is limited costs training requirements. Emerging tools, such as artificial intelligence 3D printing, enhance diagnostic accuracy precision. Despite related cost, operator training, infrastructure, techniques continue evolve, offering promising solutions care. Future research should focus on optimizing accessibility, integrating digital broaden impact minimally approaches. highlights MID's transformative role oral health outcomes ensuring sustainable, patient-focused children.

Language: Английский

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The Integration of Salivary pH Meters and Artificial Intelligence in the Early Diagnosis and Management of Dental Caries in Pediatric Dentistry: A Scoping Review

Oral, Journal Year: 2025, Volume and Issue: 5(1), P. 12 - 12

Published: Feb. 10, 2025

Dental caries is one of the most prevalent chronic conditions among children globally. Salivary pH monitoring, an essential diagnostic parameter, plays a critical role in understanding risk and oral health. This scoping review aims to evaluate application digital salivary meters pediatric dentistry, particularly diagnosis prevention, while exploring potential integration artificial intelligence (AI) this domain. Methods: A literature search was conducted across PubMed, Web Science, Scopus databases for studies published between 2014 2024. The inclusion criteria focused on clinical involving aged 1 18 years use meters. Studies that utilized AI conjunction with monitoring were also reviewed. Data extracted analyzed assess effectiveness detection their broader health applications. Results: Out 549 articles screened, 11 met criteria. highlighted utility assessing risk, dietary impacts, evaluating preventive treatments. However, none combined AI. Emerging technologies, such as smartphone-based sensors, have demonstrated promising applications real-time, non-invasive diagnostics. Conclusions: Digital provide precise reproducible measurements, significantly enhancing assessment strategies dentistry. While remains unexplored context, its refine prediction models personalize treatments underscores need future research area. These advancements could improve prevention management, outcomes.

Language: Английский

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The Transformative Role of Artificial Intelligence in Dentistry: A Comprehensive Overview. Part 1: Fundamentals of AI, and its Contemporary Applications in Dentistry

International Dental Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Artificial intelligence (AI) holds immense promise in revolutionising dentistry, spanning, diagnostics, treatment planning and educational realms. This narrative review, two parts, explores the fundamentals multifaceted potential of AI dentistry. The current article profound impact encompassing diagnostic tools, planning, patient care. Part 2 delves into education, ethics FDI communique on review begins by elucidating historical context AI, outlining its recent widespread use various sectors, including medicine fundamental concepts which entails developing machines capable executing tasks that typically necessitate human intellect. In biomedical realm, has evolved from exploring computational models to constructing systems for clinical data processing interpretation, aiming enhance medical/dental decision-making. discussion pivotal role such as Large Language Models (LLM), Vision (LVM), Multimodality (MM), revolutionizing processes documentation planning. extends applications dental specialties periodontics, endodontics, oral pathology, restorative prosthodontics, paediatric forensic odontology, maxillofacial surgery, orthodontics, orofacial pain management. AI's improving outcomes, accuracy, decision-making is evident across these specialties, showcasing transforming concludes highlighting need continued validation, interdisciplinary collaboration, regulatory frameworks ensure seamless integration paving way enhanced outcomes evidence-based practice field.

Language: Английский

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The Future of Children Oral Health: Key Trends in Pediatric Dentistry

Shiraz E-Medical Journal, Journal Year: 2025, Volume and Issue: 26(5)

Published: Feb. 15, 2025

Language: Английский

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AI-Powered Prediction of Dental Space Maintainer Needs Using X-Ray Imaging: A CNN-Based Approach for Pediatric Dentistry

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3920 - 3920

Published: April 3, 2025

Space maintainers (SMs) are essential for preserving dental arch integrity after premature tooth loss. This study aimed to develop a deep learning model predict the necessity of SMs and identify specific teeth requiring intervention. A dataset 400 X-rays was preprocessed standardize image dimensions convert them into numerical representations machine learning. The divided training (80%) testing (20%) subsets. Convolutional Neural Network (CNN) designed with multiple convolutional pooling layers, followed by fully connected layers binary classification. trained using 30 epochs evaluated accuracy, precision, recall, F1-score, ROC AUC, MCC. CNN achieved 94% precision 0.93 Class 0 (no SM needed) 0.95 1 (SM needed). AUC 0.94, MCC 0.875, indicating strong reliability. When tested on 86 X-ray images, successfully identified (showing number) SMs, minimal errors. These results suggest that proposed AI provides high-performance predictions necessity, offering valuable decision-support tool pediatric dentistry.

Language: Английский

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Usefulness of Generative Artificial Intelligence (AI) Tools in Pediatric Dentistry

Diagnostics, Journal Year: 2024, Volume and Issue: 14(24), P. 2818 - 2818

Published: Dec. 14, 2024

Background/Objectives: Generative artificial intelligence (AI) such as ChatGPT has developed rapidly in recent years, and the medical field, its usefulness for diagnostic assistance been reported. However, there are few reports of AI use dental fields. Methods: We created 20 questions that we had encountered clinical pediatric dentistry, collected responses to these from three types generative AI. The were evaluated on a 5-point scale by six specialists using Global Quality Scale. Results: average scores >3 generated tools tested; overall was 3.34. Although related “consultations guardians” or “systemic diseases” high (>3.5), score “dental abnormalities” 2.99, which lowest among four categories. Conclusions: Our results show indicating will be useful assistants field.

Language: Английский

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