Hasil untuk "Dentistry"

Yu Zhang, B. Lawn

F. Mangano, A. Gandolfi, G. Luongo et al.

Intraoral scanners (IOS) are devices for capturing direct optical impressions in dentistry. The purpose of this narrative review on the use of IOS was to: (1) identify the advantages/disadvantages of using optical impressions compared to conventional impressions; (2) investigate if optical impressions are as accurate as conventional impressions; (3) evaluate the differences between the IOS currently available commercially; (4) determine the current clinical applications/limitations in the use of IOS. Electronic database searches were performed using specific keywords and MeSH terms. The searches were confined to full-text articles written in English and published in peer-reviewed journals between January 2007 and June 2017. One hundred thirty-two studies were included in the present review; among them, 20 were previous literature reviews, 78 were in vivo clinical studies (6 randomized controlled/crossover trials, 31 controlled/comparative studies; 24 cohort studies/case series; 17 case reports) and 34 were in vitro comparative studies. Optical impressions reduce patient discomfort; IOS are time-efficient and simplify clinical procedures for the dentist, eliminating plaster models and allowing better communication with the dental technician and with patients; however, with IOS, it can be difficult to detect deep margin lines in prepared teeth and/or in case of bleeding, there is a learning curve, and there are purchasing and managing costs. The current IOS are sufficiently accurate for capturing impressions for fabricating a whole series of prosthetic restorations (inlays/onlays, copings and frameworks, single crowns and fixed partial dentures) on both natural teeth and implants; in addition, they can be used for smile design, and to fabricate posts and cores, removable partial prostheses and obturators. The literature to date does not support the use of IOS in long-span restorations with natural teeth or implants. Finally, IOS can be integrated in implant dentistry for guided surgery and in orthodontics for fabricating aligners and custom-made devices.

R. Sabino-Silva, A. Jardim, W. Siqueira

A novel coronavirus (COVID-19) is associated with humanto-human transmission. The COVID-19 was recently identified in saliva of infected patients. In this point-of-view article, we discuss the potential of transmission via the saliva of this virus. The COVID-19 transmission via contact with droplets and aerosols generated during dental clinical procedures is expected. There is a need to increase investigations to the detection of COVID-19 in oral fluids and its impact on the transmission of this virus, which is crucial to improve effective strategies for prevention, especially for dentists and healthcare professionals that perform aerosol-generating procedures. Saliva can have a pivotal role in the human-to-human transmission, and non-invasive salivary diagnostics may provide a convenient and cost-effective point-of-care platform for the fast and early detection of COVID-19 infection.

T. Shan, F. R. Tay, L.S. Gu

Artificial intelligence (AI) is a technology that utilizes machines to mimic intelligent human behavior. To appreciate human-technology interaction in the clinical setting, augmented intelligence has been proposed as a cognitive extension of AI in health care, emphasizing its assistive and supplementary role to medical professionals. While truly autonomous medical robotic systems are still beyond reach, the virtual component of AI, known as software-type algorithms, is the main component used in dentistry. Because of their powerful capabilities in data analysis, these virtual algorithms are expected to improve the accuracy and efficacy of dental diagnosis, provide visualized anatomic guidance for treatment, simulate and evaluate prospective results, and project the occurrence and prognosis of oral diseases. Potential obstacles in contemporary algorithms that prevent routine implementation of AI include the lack of data curation, sharing, and readability; the inability to illustrate the inner decision-making process; the insufficient power of classical computing; and the neglect of ethical principles in the design of AI frameworks. It is necessary to maintain a proactive attitude toward AI to ensure its affirmative development and promote human-technology rapport to revolutionize dental practice. The present review outlines the progress and potential dental applications of AI in medical-aided diagnosis, treatment, and disease prediction and discusses their data limitations, interpretability, computing power, and ethical considerations, as well as their impact on dentists, with the objective of creating a backdrop for future research in this rapidly expanding arena.

Danial Khorsandi, Amir Fahimipour, P. Abasian et al.

3D and 4D printing are cutting-edge technologies for precise and expedited manufacturing of objects ranging from plastic to metal. Recent advances in 3D and 4D printing technologies in dentistry and maxillofacial surgery enable dentists to custom design and print surgical drill guides, temporary and permanent crowns and bridges, orthodontic appliances and orthotics, implants, mouthguards for drug delivery. In the present review, different 3D printing technologies available for use in dentistry are highlighted together with a critique on the materials available for printing. Recent reports of the application of these printed platformed are highlighted to enable readers appreciate the progress in 3D/4D printing in dentistry.

Xinru Ma, Shiyu Zhou, Xiaoling Xu et al.

Copper has been used as an antimicrobial agent long time ago. Nowadays, copper-containing nanoparticles (NPs) with antimicrobial properties have been widely used in all aspects of our daily life. Copper-containing NPs may also be incorporated or coated on the surface of dental materials to inhibit oral pathogenic microorganisms. This review aims to detail copper-containing NPs’ antimicrobial mechanism, cytotoxic effect and their application in dentistry.

Manjinder Singh, Suvansh Gupta, Shanta Chopra et al.

The term LASER is a cipher for Light Amplification by the Stimulated Emission of Radiation. They are used as a niche tool as a direct replacement for conventional approaches such as scalpels and blades. Irrespective of its types, lasers have shown tremendous results in dentistry. This article provides a comprehensive review of the wide applications of lasers in different fields of dentistry.

Paridhi Agrawal, P. Nikhade

Artificial intelligence (AI) has remarkably increased its presence and significance in a wide range of sectors, including dentistry. It can mimic the intelligence of humans to undertake complex predictions and decision-making in the healthcare sector, particularly in endodontics. The models of AI, such as convolutional neural networks and/or artificial neural networks, have shown a variety of applications in endodontics, including studying the anatomy of the root canal system, forecasting the viability of stem cells of the dental pulp, measuring working lengths, pinpointing root fractures and periapical lesions and forecasting the success of retreatment procedures. Future applications of this technology were considered in relation to scheduling, patient care, drug-drug interactions, prognostic diagnosis, and robotic endodontic surgery. In endodontics, in terms of disease detection, evaluation, and prediction, AI has demonstrated accuracy and precision. AI can aid in the advancement of endodontic diagnosis and therapy, which can enhance endodontic treatment results. However, before incorporating AI models into routine clinical operations, it is still important to further certify the cost-effectiveness, dependability, and applicability of these models.

F. Carrillo-Perez, O. Pecho, J. Morales et al.

OBJECTIVE To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research. MATERIALS AND METHODS The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years. RESULTS Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling. CONCLUSIONS The insight provided by the present work has reported outstanding results in the design of high-performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations. CLINICAL SIGNIFICANCE The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.

Naseer Ahmed, M. Abbasi, Filza Zuberi et al.

Objective The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

Agata Ossowska, A. Kusiak, D. Świetlik

Nowadays, artificial intelligence (AI) is becoming more important in medicine and in dentistry. It can be helpful in many fields where the human may be assisted and helped by new technologies. Neural networks are a part of artificial intelligence, and are similar to the human brain in their work and can solve given problems and make fast decisions. This review shows that artificial intelligence and the use of neural networks has developed very rapidly in recent years, and it may be an ordinary tool in modern dentistry in the near future. The advantages of this process are better efficiency, accuracy, and time saving during the diagnosis and treatment planning. More research and improvements are needed in the use of neural networks in dentistry to put them into daily practice and to facilitate the work of the dentist.

Qiang He, Wentian Qu, Jiajia Dai et al.

Accurate semantic segmentation of 3D dental models is essential for digital dentistry applications such as orthodontics and dental implants. However, due to complex tooth arrangements and similarities in shape among adjacent teeth, existing methods struggle with accurate segmentation, because they often focus on local geometry while neglecting global contextual information. To address this, we propose TCATSeg, a novel framework that combines local geometric features with global semantic context. We introduce a set of sparse yet physically meaningful superpoints to capture global semantic relationships and enhance segmentation accuracy. Additionally, we present a new dataset of 400 dental models, including pre-orthodontic samples, to evaluate the generalization of our method. Extensive experiments demonstrate that TCATSeg outperforms state-of-the-art approaches.

R. Rokhshad, M. Ducret, A. Chaurasia et al.

OBJECTIVE Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy, improve patient outcomes and streamline workflows. The present study provides a framework and a checklist to evaluate AI applications in dentistry from this perspective. METHODS Lending from existing guidance documents, an initial draft of the checklist and an explanatory paper were derived and discussed among the groups members. RESULTS The checklist was consented to in an anonymous voting process by 29 group members. Overall, 11 principles were identified (diversity, transparency, wellness, privacy protection, solidarity, equity, prudence, law and governance, sustainable development, accountability, and responsibility, respect of autonomy, decision-making). CONCLUSIONS Providers, patients, researchers, industry, and other stakeholders should consider these principles when developing, implementing, or receiving AI applications in dentistry. CLINICAL SIGNIFICANCE While AI has become increasingly commonplace in dentistry, there are ethical concerns around its usage, and users (providers, patients, and other stakeholders), as well as the industry should consider these when developing, implementing, or receiving AI applications based on comprehensive framework to address the associated ethical challenges.

S. Vishwanathaiah, Hytham N. Fageeh, S. Khanagar et al.

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan.

Talal Bonny, Wafaa Al Nassan, Khaled Obaideen et al.

Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.

Ashwini Dhopte, Hiroj Bagde

Artificial intelligence (AI) has emerged as a transformative technology in various industries, and its potential in dentistry is gaining significant attention. This abstract explores the future prospects of AI in dentistry, highlighting its potential to revolutionize clinical practice, improve patient outcomes, and enhance the overall efficiency of dental care. The application of AI in dentistry encompasses several key areas, including diagnosis, treatment planning, image analysis, patient management, and personalized care. AI algorithms have shown promising results in the automated detection and diagnosis of dental conditions, such as caries, periodontal diseases, and oral cancers, aiding clinicians in early intervention and improving treatment outcomes. Furthermore, AI-powered treatment planning systems leverage machine learning techniques to analyze vast amounts of patient data, considering factors like medical history, anatomical variations, and treatment success rates. These systems provide dentists with valuable insights and support in making evidence-based treatment decisions, ultimately leading to more predictable and tailored treatment approaches. While the potential of AI in dentistry is immense, it is essential to address certain challenges, including data privacy, algorithm bias, and regulatory considerations. Collaborative efforts between dental professionals, AI experts, and policymakers are crucial to developing robust frameworks that ensure the responsible and ethical implementation of AI in dentistry. Moreover, AI-driven robotics has introduced innovative approaches to dental surgery, enabling precise and minimally invasive procedures, and ultimately reducing patient discomfort and recovery time. Virtual reality (VR) and augmented reality (AR) applications further enhance dental education and training, allowing dental professionals to refine their skills in a realistic and immersive environment. AI holds tremendous promise in shaping the future of dentistry. Through its ability to analyze vast amounts of data, provide accurate diagnoses, facilitate treatment planning, improve image analysis, streamline patient management, and enable personalized care, AI has the potential to enhance dental practice and significantly improve patient outcomes. Embracing this technology and its future development will undoubtedly revolutionize the field of dentistry, fostering a more efficient, precise, and patient-centric approach to oral healthcare. Overall, AI represents a powerful tool that has the potential to revolutionize various aspects of society, from improving healthcare outcomes to optimizing business operations. Continued research, development, and responsible implementation of AI technologies will shape our future, unlocking new possibilities and transforming the way we live and work.

Suyang Chen, Cai Yu

Introduction: An oroantral fistula (OAF) is an abnormal connection between the oral cavity and the maxillary sinus, usually occurred after the removal of maxillary premolar and molar teeth. Many techniques have been described for closure of oroantral fistulas but ignoring restoration of bony defects secondary to OAFs. This report presents a novel three-layered method for repairing OAFs with biomaterials sandwiched between the maxillary sinus floor mucosa and the palatal flap. Case description: A 59-year-old female patient was admitted to clinic with an oroantral fistula, of which the diameter was 6 mm. Firstly, peripheral soft tissue of the fistula was utilized to repair the maxillary sinus floor mucosa. And then, a mineralized collagen plug was placed over the sinus mucosa. Finally, the fistula was completely covered by a palatal flap. The follow-up period lasted for 6 months to evaluate the closure of the OAF and bone regeneration. Discussion: To yield adequate bone, a mineralized collagen plug was used to maintain space and promote bone generation. Compared with a buccal flap, a pedicled palatal flap has advantages of offering well-keratinized gingiva, not reducing the ridge height and better blood supply, thus ensuring success of both the closure of OAFs and the subsequent implant placement. Conclusion/clinical significance: The closure was successfully achieved without any signs of inflammation in the maxillary sinus and regenerative bone was observed after 6 months. The triple-layered technique is an effective procedure to repair OAFs.

Masaaki Yamada, Michikazu Sekine, Takashi Tatsuse et al.

Abstract Background Dental caries is the most prevalent disease in elementary schoolchildren in Japan. Problematic Internet use (PIU) has increased among children; however, its association with caries has rarely been studied. We aimed to explore (1) sex differences in dental caries and (2) the association of dental caries with lifestyle and PIU among elementary school children in Japan. Methods From 110 elementary schools in Toyama Prefecture, 13,413 children in the 4th-6th grades (mean age, 10.5 years) participated in the Toyama Safe Internet Use Project in 2018. We inquired about lifestyle, anthropometric data, family rules for screen time, PIU, and the number of self-reported treated caries. PIU was assessed using the Young’s Diagnostic Questionnaire. We defined children having ≥ 3 caries as having multiple caries. Subsequently, a modified Poisson regression analysis was performed. Results Overall, 12,146 children (90.7%) were analyzed. The prevalence of multiple caries was 25.7% (24.4% in boys and 27.0% in girls). In the regression analysis, the presence of multiple caries was significantly associated with being a girl(adjusted prevalence ratio (aPR) 1.13), being in higher grades (5th grade: aPR 1.13 and 6th grade: aPR 1.14), skipping breakfast (aPR 1.11), having late bedtime (10 to 11 p.m.: aPR 1.17 and ≥ 11 p.m.: aPR 1.23), tooth brushing (once a day: aPR 1.14 and not every day: aPR 1.41), having no family rules (aPR 1.20), and PIU (YDQ score 3–4: aPR 1.17). When stratified by sex, a dose-response relationship was observed between PIU and the presence of multiple caries in boys (YDQ score 3–4: aPR 1.19 and YDQ score ≥ 5: aPR 1.22). Conclusion Being a girl, having an undesirable lifestyle, and PIU were significantly associated with multiple self-reported caries. In addition to a having a healthy lifestyle, restricting PIU is recommended to prevent caries in children.

Zabin K. Bagewadi, Gouri H. Illanad, T. M. Yunus Khan et al.

Abstract The current investigation reports anti-cancer, antioxidant and antibacterial potential of L-Glutaminase (Streptomyces roseolus strain ZKB1) and L-Glutaminase capped nanoparticles. The highest L-Glutaminase production of 9.57 U/mL was achieved on the 4th day of fermentation when L-Glutamine was used as the sole carbon and nitrogen source. Enhanced recycling stability was observed after 6 cycles using L-Glutaminase immobilized in 3% agar and agarose matrices. Free and immobilized L- Glutaminase showed K m of 13.89 ± 0.8 and 7.13 ± 0.3 mM and V max of 18.40 ± 1.5 and 24.21 ± 1.7 U/mg respectively. L- Glutaminase capped silver (AgNP) and zinc oxide (ZnONP) nanoparticles were synthesized and structurally characterized using UV visible spectroscopy, FTIR, SEM–EDS, XRD and AFM. L- Glutaminase capped AgNP and ZnONP exhibited good thermal stability with five and three stages weight loss pattern respectively based on TGA. L-Glutaminase capped AgNP exhibited highest inhibitory activity against B. subtilis (45 $$\pm$$ ± 0.5 mm) and E. coli (33 $$\pm$$ ± 0.8 mm) whereas, L-Glutaminase capped ZnONP demonstrated highest inhibition against E. coli (30 $$\pm$$ ± 0.3 mm) and B. cereus (25 $$\pm$$ ± 0.5 mm). Increased nanoparticles concentration exhibited increased inhibitory potential as compared to wild L-Glutaminase and lowest MIC of 0.09 µg/mL was exhibited against B. cereus. L-Glutaminase capped nanoparticles demonstrated significant antioxidant properties through in-vitro ABTS and DPPH radical scavenging assays in a dosage-dependent manner. L-Glutaminase and capped AgNP and ZnONP, demonstrated pronounced cell cytotoxicity against MCF-7 cancerous cell line with 57.17 µg/mL, 8.13 µg/mL and 28.31 µg/mL IC50 values respectively, suggesting promising properties as anticancer agents in enzyme-based therapy. The results reveal promising biological activities with potential applications in healthcare sector. Graphical Abstract

Hoi-Jeong Lim

Recently, importance of meta-analysis is increasing in the field of dentistry, since it is not easy to settle controversies arising from conflicting studies. Meta-analysis is the statistical method of combining results from two or more individual studies that have been done on the same topic. Merits of meta-analysis includes an increase in power, an improvement in precision, and the ability to address solution not provided by individual studies. However, it might mislead researchers when variation across studies and publication bias are not carefully taken into consideration. The purpose of this study is to help understand meta-analysis by making use of individual results in dental research paper.