European Archives of Paediatric Dentistry, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 8, 2024
Language: Английский
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
Citations
2
Dental Traumatology, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 11, 2024
ABSTRACT Dental trauma is highly prevalent, involving 25% of school‐age children and about 12.5% the general population world. Due to young age patients that are usually involved in dental trauma, there tooth‐related complicating factors, such as open apices, thin dentinal walls, unfavorable crown‐to‐root ratio, well patient‐related anxiety cooperation, other challenges related complex diagnosis treatment. Therefore, it not surprising global status knowledge for prevention emergency management traumatic injuries among professionals was often reported insufficient. Aiming improve education, one should consider contemporary educational settings have transitioned a digital learning ecosystem current students belong unique generational cohort. this paper examines educators encounter school classrooms defining characteristics generation Y Z student cohorts. Finally, outlines strategies optimize learning, considering students.
Language: Английский
Citations
4
Dental Traumatology, Journal Year: 2025, Volume and Issue: 41(2), P. 129 - 132
Published: March 14, 2025
Several factors are associated with dental trauma (DT) occurrence, and these well-established in the literature [1, 2]. However, new studies hypotheses suggest that a lack of balance is positively falls children older individuals [3, 4]. In this issue Lunardelli et al. investigated relationship between orthostatic occurrence DT 6-year-old school Brazil [5]. The study emphasizes connection reduced an increased risk falls, identifying it as factor etiology children. This highlights need for preventive measures focused on creating safer environments, particularly schools, involving multidisciplinary team to support school-aged minimizing trauma. Traumatic injuries (TDI) highly prevalent during childhood, primary dentition [6, 7]. Although TDI recognized common issue, influencing its prevalence preschool-aged have been poorly understood [8, 9]. Rivera López through cohort 4-year-old from South [10]. Using directed acyclic graphs (DAGs), researchers developed theoretical model explore complex relationships among potential factors, including demographic, behavioral, environmental variables. provides insights into multifactorial nature young children, offering foundation targeted prevention early intervention strategies. By applying advanced analytical techniques, contribute deeper understanding causes broader implications pediatric oral health. Autotransplanted teeth demonstrated remarkable survival rate over 95% [11-13]. standardization precision quantifying root development results inconsistent findings impedes comparisons studies. Traditional analysis methods based two-dimensional radiographs shows significant limitations, such image overlap, patient positioning challenges, low measurement accuracy. Cone-beam computed tomography (CBCT) might provide more accurate detailed analysis, regions like periapical areas [14]. Beltrame proposed methodology assessing measuring length using CBCT 12 patients [15]. highlighted CBCT's superiority conventional radiography evaluating after autogenous tooth transplants. method, any radiographic tool, should be assessed terms radiation risks vs. suggested benefits. Advances 3D-printed replicas improvements efficiency procedures, autotransplantation [16-18]. most evidence supporting outcomes comes observational studies, case reports, limited number case–control Consequently, there insufficient data controlled clinical trials biological efficacy (i.e., long-term radiological outcomes), limiting impact technologies. Lejnieks combined 3D replica protocol trial. goal was investigate 1 year follow-up, providing stronger benefits technologies molar [19]. investigation underscores protocols enhance surgical serve valuable training tools, calling further address current limitations their applications practice. Artificial Intelligence (AI) has emerged resource, information clinicians seeking online healthcare knowledge medical decision-making [20, 21]. rigorous evaluations accuracy consistency responses provided by AI Google Gemini, context managing traumatized permanent teeth, still lacking. hold transform access information, concerns remain regarding reliability biases. Previous tools Bard, experimental version less consistent compared other models, ChatGPT, topics related endodontics [22]. Portilla evaluated about management Gemini those experienced academic endodontists. set predefined questions, they conducted comprehensive comparison [23]. suggests become accessible tool professionals. improving database algorithms crucial enhancing topics. Advancing refinement essential ensure reliable robust future. Furthermore Johnson aimed assess validity chatbots, Bing, ChatGPT 3.5, Claude AI, addressing frequently asked questions [24]. Ensuring secure distribution field trauma, requires authorities establish clear guidelines regulations governing chatbot use. Collaborative efforts ethical platforms. Public remains [25, 26]. advancements now able deliver public health helps professionals deal issues avulsions. Large language models (LLMs) offer education, however, since fine-tuned human feedback, may biased or incorrect, answers avulsion [20]. Tokgöz Kaplan Cankar verified comprehensiveness Gemini. Four dentist reviewers scored according IADT [27]. evaluation revealed although both potential, quality necessary answers. Avulsion one severe types [28]. Treatment prompt correct emergency management, depends viability periodontal ligament (PDL) cells [29]. can cause PDL, dehydration structural damage fibers [30]. For reason, storing avulsed appropriate medium help preserve prevent breakdown [31]. According International Association Dental Traumatology (IADT), saline, saliva, milk considered natural solutions maintain PDL before replantation [32]. Lee effects six media fibroblasts (PDLF). included Hank's Balanced Salt Solution (HBSS), HBSS supplemented ascorbic acid (Vitamin C), platelet-derived growth (PDGF), combination PDGF acid, platelet lysate, Dulbecco's Modified Eagle Medium [33]. modified mixtures were ability PDLF success procedures. could our overall future considerations proper storage teeth. Central incisors affected [34, 35], especially cases proclined maxillary anterior [36]. Various available different activities age groups [37, 38]. use mouthguards method sports. Different manufacturing exist [39]; custom-made professionally crafted, better fit and, some improved cardiopulmonary capacity athletes. Bhadule created finite element (FEA) scan 12-year-old male [40]. They simulated actual without mouthguard. emphasized importance properly fitted protecting against maxillofacial reducing stress magnitude, dentitions Mouthguards also play role soft tissues sports high-risk [41, 42]. commonly used include stock mouthguards, mouth-formed options, each varying levels comfort protection 43]. despite widespread use, made materials not sufficient shock absorption, durability, user [44, 45]. Therefore, growing alternative develop performance, improve experience, promote adoption. Nassani absorption capacities thermoformed ethylene vinyl acetate (EVA) polyolefin dentistry [46]. toughness traditional EVA sports, highlighting material. Furthermore, fabricated adequate uniform thickness reduce strain produced [47, 48]. Some production processes mouthguards. mouthguard significantly impacts protect effectiveness. single-layered often longitudinal dimensional stability, leading athletes increasingly double-layered [49], which best option [50]. Uma final methods, puncturing technique and/or cooldown period pressing second sheet [51]. fabrication techniques Fiber splint stabilization vital secondary promoting favorable healing due flexibility distribute effectively [52, 53]. Their mastication, advantage [54], making them key component effective [55]. While many stress-distributing properties fiber splints research focusing effectiveness mastication limited. Specifically, whether incisal cervical region unclear. gap restricts optimization treatment approaches biomechanical behavior under dynamic occlusal forces. Ding how splints, either region, affects [56]. Utilizing FEA, placement, contributing strategies traumatic injuries.
Language: Английский
Citations
0
Journal of International Dental Sciences, Journal Year: 2025, Volume and Issue: 11(1), P. 22 - 31
Published: March 27, 2025
Aim: This study aimed to evaluate the reliability and consistency of four artificial intelligence (AI) chatbots—ChatGPT 3.5, Google Gemini, Bing, Claude AI—as public sources information on management primary tooth trauma. Materials Methods: A total 31 dichotomous questions were developed based common issues concerns related dental trauma, particularly those frequently raised by parents. Each question, sequentially presented AI chatbots, was repeated three times daily, with a one-hour interval between repetitions, over five-day period, assess reproducibility responses. Accuracy determined calculating proportion correct responses, 95% confidence intervals estimated using Wald binomial method. Reliability assessed Fleiss’ kappa coefficient. Results: All chatbots demonstrated high accuracy. Bing emerged as most accurate model, achieving an accuracy rate 96.34%, while had lowest at 88.17%. Consistency classified “almost perfect” for ChatGPT, whereas exhibited “substantial” level agreement. These findings underscore relative performance models in tasks requiring reliability. Conclusion: results emphasize importance critically evaluating AI-based systems their potential use clinical applications. Continuous improvements updates are essential enhance ensure effectiveness tools.
Language: Английский
Citations
0
Dental Traumatology, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Artificial intelligence (AI) chatbots, also known as large language models (LLMs), have become increasingly common educational tools in healthcare. Although the use of LLMs for emergency dental trauma is gaining popularity, it crucial to assess their reliability. This study aimed compare reliabilities different response multiple questions related trauma. In a cross-sectional observational conducted October 2024, 30 (10 multiple-choice, 10 fill-in-the-blank, and dichotomous) based on International Association Dental Traumatology guidelines were posed five LLMs: ChatGPT 4, 3.5, Copilot Free version (Copilot F), Pro P), Google Gemini over nine consecutive days. Responses each model (1350 total) recorded binary format analyzed using Pearson's chi-square Fisher's exact tests correctness consistency (p < 0.05). The answers provided by repeated days showed high degree repeatability. there was no statistically significant difference success rate providing correct among > 0.05), rankings successful follows: 3.5 (76.7%) P (73.3%) F (70%) 4 (63.3%) (46.7%). significantly higher choice fill blank compared performance dichotomous (true/false) Conversely, did not exhibit differences across question types. Notably, explanations often inaccurate, Copilot's cited references had low evidential value. While show potential adjunct traumatology, variable accuracy inclusion unreliable call careful integration strategies.
Language: Английский
Citations
0
Systems, Journal Year: 2025, Volume and Issue: 13(4), P. 281 - 281
Published: April 10, 2025
The integration of large language models (LLMs) into remote healthcare has the potential to revolutionize medication management by enhancing communication, improving adherence, and supporting clinical decision-making. This study aims explore role LLMs in management, focusing on their impact. paper comprehensively reviews existing literature, medical LLM cases, commercial applications healthcare. It also addresses technical, ethical, regulatory challenges related use artificial intelligence (AI) this context. review methodology includes analyzing studies applications, comparing impact, identifying gaps for future research development. reveals that have shown significant communication between patients providers, adherence monitoring, decision-making management. Compared traditional reminder systems, AI systems a 14% higher rate rates pilot studies. However, there are notable challenges, including data privacy concerns, system issues, ethical dilemmas AI-driven decisions such as bias transparency. Overall, offers comprehensive analysis both transformative key be addressed. provides insights policymakers, researchers optimizing
Language: Английский
Citations
0
Dental Traumatology, Journal Year: 2025, Volume and Issue: unknown
Published: April 15, 2025
ABSTRACT Background/Aim This study aims to review contents related dental maxillofacial trauma (DMT) in the curricula of Southeast Asian (SEA) countries and assess their effectiveness equipping future professionals with necessary skills for efficient management DMT. Additionally, describe how academics involved planning organization these envision incorporation DMT within education. Methods The employed a mixed methods approach composed two phases. Phase 1 all printed documentation explore curricula, including details such as country, subject, year study, coverage, time spent on assessment types various training themes (e.g., management, surgical, prevention). In 2, semi‐structured interviews were conducted responsible curriculum development each school identify they envisaged into curricula. Results Regarding curricular contents, dataset comprised total 31 subjects concerning contents. Findings revealed variability coverage education across institutions, lack practical need better integration collaboration among different specialties. narrative highlighted concerns about insufficient hands‐on practice available managing DMT, suggesting that students may not have enough opportunities experience this area. deficit could potentially impact ability effectively manage cases clinical setting. Conclusion provides valuable insights current state SEA countries, identifying critical areas improvement potential strategies enhancing effectiveness. It emphasizes importance integrating collaborative learning equip thereby addressing significant challenges faced by educators practitioners SEA.
Language: Английский
Citations
0
Journal of Endodontics, Journal Year: 2025, Volume and Issue: unknown
Published: May 1, 2025
Language: Английский
Citations
0
BMC Oral Health, Journal Year: 2025, Volume and Issue: 25(1)
Published: May 22, 2025
Language: Английский
Citations
0
European Archives of Paediatric Dentistry, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 8, 2024
Language: Английский
Citations
0