Artificial Intelligence in Orthodontic Smart Application for Treatment Coaching and Its Impact on Clinical Performance of Patients Monitored with AI-TeleHealth System

Unveiling the role of artificial intelligence applied to clear aligner therapy: A scoping review

OBJECTIVES

To conduct a scoping review on the application of artificial intelligence (AI) in clear aligner therapy and to assess the extent of AI integration and automation in orthodontic software currently available to orthodontists.

DATA AND SOURCES

A systematic electronic literature search was performed in the following databases: PubMed, Embase, Web of Science, Cochrane Library, and Scopus. Also, grey literature resources up to March 2024 were reviewed. English-language studies on potential AI applications for clear aligner therapy were included based on an independent evaluation by two reviewers. An assessment of the automation steps in orthodontic software available on the market up to March 2024 was also conducted.

STUDY SELECTION AND RESULTS

Out of 708 studies, 41 were included. Sixteen articles focused on tooth segmentation, four on registration of digital models, 13 on digital setup, and eight on remote monitoring. Moreover, 13 aligner software programs were identified and assessed for their level of automation. Only one software demonstrated complete automation of the steps involved in the orthodontic digital workflow.

CONCLUSIONS

None of the 13 identified aligner software programs were evaluated in the 41 included studies. However, AI-based tooth segmentation achieved 98 % accuracy, while AI effectively merged CBCT and IOS data, supported digital measurements, predicted treatment outcomes, and showed potential for remote monitoring.

CLINICAL SIGNIFICANCE

AI applications in clear aligner therapy are on the rise. This scoping review enables orthodontists to identify AI-based solutions in orthodontic planning and understand its implications, which can potentially enhance treatment efficiency, accuracy, and predictability.

Cariogenic Dietary Assessment Using a Mobile App in Children

PURPOSE

A direct association exists between caries and high-sugar diets. The aim of this study was to test whether the cariogenicity of diet assessed and analysed through a new mobile app is associated with caries risk among children.

MATERIALS AND METHODS

A total of 247 children, 2-15 years old, were recruited from university and hospital daycare centers and dental clinics. Diet was assessed via a 24-h recall, and caries (dmft/DMFT- ICDAS criteria) was documented through clinical examination. A mobile app was designed to analyse dietary data and calculate the diet's cariogenicity. Demographics, daily meals, meal duration and type, and toothbrushing were entered. A diagram presenting an estimate of the oral pH was produced, showing the time interval during which caries may develop, and a calculated cariogenic dietary risk was generated. Multivariate logistic regression derived odds ratios estimating associations between the cariogenic diet and caries across three age groups.

RESULTS

A cariogenic diet analysed by the app was positively associated with dfmt (r = 0.477, p 0.001) in 2- to 6-year-old children, with dmft (r = 0.376, p 0.05) and DMFT (r = 0.271, p 0.05) in 7- to 11-year-old children, and with DMFT (r = 0.383, p 0.001) in 12- to 15-year-old children. Parents' lower educational level was associated with a statistically significantly higher caries risk in younger children (p 0.05).

CONCLUSION

Cariogenic diet evaluated with the new app was associated with increased caries, providing evidence of an accurate assessment among children. This app could assist dentists in providing dietary assessment and advice related to caries risk at the dental office in a more structured, educational, and time-saving way.

A questionnaire study regarding knowledge, attitude and usage of artificial intelligence and machine learning by the orthodontic fraternity of Northern India

Aim

The aim of the questionnaire study was to determine the knowledge, attitude, and perception of orthodontists regarding the role of artificial intelligence in dentistry in general and orthodontics specifically, and to determine the use of artificial intelligence by the orthodontist.

Methods

This cross-sectional study was done among the orthodontists of Northern India (clinicians, academicians, and postgraduates) through a web-based electronic survey using Google Forms. The study was designed to obtain information about AI and its basic usage in daily life, in dentistry, and in orthodontics from the participants. The options given were set specifically according to the Likert scale to maintain the correct format. The questionnaire was validated by one AI expert and one orthodontic expert, followed by pretesting in a smaller group of 25 orthodontists 2 weeks before circulation. A total of 100 orthodontists and postgraduate students responded to the pretested online questionnaire link for 31 questions in four sections sent via social media websites in a period of 3 months.

Results

The majority of the participants believe that AI could be useful in diagnosis and treatment planning and could revolutionize dentistry in general. 84 % of the orthodontic academicians and clinicians, including PG students, consider AI a useful tool for boosting performance and delivering quality care in orthodontics, and 72 % see AI as a partner rather than a competitor in the foreseeable future of dentistry. 90 % of the participants believe that the incorporation of AI into CBCT analysis can be a valuable addition to diagnosis and treatment planning. 86 % of total participants agree that AI can be helpful in decision-making for orthognathic surgery, and 84 % find AI useful for bone age assessment.

Conclusions

It was observed that academicians are more aware of AI terminologies and usage as compared to PG students and clinicians. There is a consensus that AI is a useful tool for diagnosis and treatment planning, boosting performance and quality care in orthodontics. In spite of these facts, 62.5 % of clinicians and 40 % of PG students are still not using AI for cephalometric analysis (p = 0.033).

Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial Surgery: A Comprehensive Analysis of Published Works

Artificial intelligence (AI), deep learning (DL), and machine learning (ML) are computer, machine, and engineering systems that mimic human intelligence to devise procedures. These technologies also provide opportunities to advance diagnostics and planning in human medicine and dentistry. The purpose of this literature review was to ascertain the applicability and significance of AI and to highlight its uses in maxillofacial surgery. Our primary inclusion criterion was an original paper written in English focusing on the use of AI, DL, or ML in maxillofacial surgery. The sources were PubMed, Scopus, and Web of Science, and the queries were made on the 31 December 2023. The search strings used were "artificial intelligence maxillofacial surgery", "machine learning maxillofacial surgery", and "deep learning maxillofacial surgery". Following the removal of duplicates, the remaining search results were screened by three independent operators to minimize the risk of bias. A total of 324 publications from 1992 to 2023 were finally selected. These were calculated according to the year of publication with a continuous increase (excluding 2012 and 2013) and R2 = 0.9295. Generally, in orthognathic dentistry and maxillofacial surgery, AI and ML have gained popularity over the past few decades. When we included the keywords "planning in maxillofacial surgery" and "planning in orthognathic surgery", the number significantly increased to 7535 publications. The first publication appeared in 1965, with an increasing trend (excluding 2014-2018), with an R2 value of 0.8642. These technologies have been found to be useful in diagnosis and treatment planning in head and neck surgical oncology, cosmetic and aesthetic surgery, and oral pathology. In orthognathic surgery, they have been utilized for diagnosis, treatment planning, assessment of treatment needs, and cephalometric analyses, among other applications. This review confirms that the current use of AI and ML in maxillofacial surgery is focused mainly on evaluating digital diagnostic methods, especially radiology, treatment plans, and postoperative results. However, as these technologies become integrated into maxillofacial surgery and robotic surgery in the head and neck region, it is expected that they will be gradually utilized to plan and comprehensively evaluate the success of maxillofacial surgeries.

Awareness and usage of mobile applications as an orthodontic diagnostic tool among Croatian orthodontic clinicians

OBJECTIVE

To assess the impact of gender and orthodontic qualification length on the awareness, knowledge and usage of orthodontic diagnostic mobile applications, non-diagnostic mobile applications and social media platforms among orthodontic clinicians.

DESIGN

Cross-sectional questionnaire-based study.

SETTING

The Republic of Croatia.

PARTICIPANTS

A total of 92 orthodontic specialists, members of the Croatian Dental Chamber.

METHODS

This study was conducted using a questionnaire distributed via email to orthodontic clinicians between May and July 2022.

RESULTS

In total, 92 respondents were divided into groups according to sex and median orthodontic qualification length: more recently qualified (MRQ) with ⩽12 years; and longer qualified (LQ) with >12 years. Nearly one-third of respondents did not have any prior knowledge of mobile applications used as an orthodontic diagnostic tool. MRQ respondents were more interested in using mobile apps as opposed to computer software for digital analysis (P < 0.05). This interest was in a negative correlation with orthodontic qualification length (P < 0.01) and was more prevalent among female respondents (P < 0.001). About one-third (32.6%) of respondents did not use non-diagnostic mobile applications and 44.6% did not use social media platforms. Nearly two-thirds (62%) of the respondents did not promote their work through social media. Male respondents and LQ promoted their work more frequently than others (P < 0.05). The usage of other mobile applications was in a positive correlation with the knowledge and awareness of orthodontic mobile applications (P < 0.05).

CONCLUSION

Orthodontic clinicians lacked knowledge, awareness and the usage of orthodontic diagnostic mobile applications according to sex and orthodontic qualification length. One-third used non-diagnostic mobile applications and less than half used social platforms in daily clinical work.

Awareness and Periodontal Health Practices of Fixed Orthodontic Appliance Patients: A Questionnaire-Based Survey

A well-aligned dentition is more conducive to periodontal health, which is necessary for successful orthodontic therapy. Maintaining good dental hygiene is crucial for effective treatment, and patient cooperation, education, motivation, and attitude are all important components. Orthodontists must routinely check in with their patients to see whether they are maintaining their oral hygiene and if they are using any additional assistance. Negligence on the part of the patient may be the cause of poor treatment outcomes. This study aims to show how patient education can affect treatment outcomes and the development of a functional, aesthetically pleasing, and healthy dentition. Aim This study aims to investigate awareness, attitude, and periodontal health knowledge among orthodontic patients. Objectives The study explores the level of awareness and knowledge regarding periodontal health among orthodontic patients, examining its correlation with factors such as age, attitude, and duration of orthodontic treatment. Additionally, it aims to gauge the extent of education received by orthodontic patients regarding proper oral hygiene practices and the potential repercussions of neglecting them. Methods A questionnaire-based study with a cross-sectional design was performed in Jeddah, Saudi Arabia. A total of 428 participants were randomly selected from several private orthodontic clinics and hospitals. The participants in the study were individuals currently undergoing treatment with fixed orthodontic appliances. Information was gathered using a self-administered questionnaire. Results The patients undergoing orthodontic treatment have a moderate understanding of periodontal disease about dental plaque. The level of awareness of periodontal health was 41%, and the level of knowledge about periodontal health was 51%. When it came to periodontal health, adult orthodontic patients had a positive attitude toward fixed orthodontic treatment (mean score = 0.75). Subjects' attitudes regarding fixed orthodontic treatment were significantly impacted by the patient's consistency with his/her dental checkups (p value = 0.02). Conclusion The patients' periodontal health awareness was moderate, while their periodontal health knowledge was fair. Orthodontic patient's awareness levels, as well as knowledge levels, showed significant differences in age and duration but not sex. Results showed no significant difference among the attitude levels of orthodontic patients and age, sex, and duration.

Emerging Technologies in Hand Orthopedic Surgery: Current Trends and Future Directions

Emerging technologies are changing hand surgery by improving surgical precision, minimizing tissue disruption, and expediting patient recovery. These advancements have the potential to revolutionize surgical procedures, patient outcomes, and rehabilitation processes. However, there are still challenges that need to be addressed before these technologies can be widely adopted. These challenges include the learning curve for surgeons, high costs, and ethical considerations. Future research should focus on addressing the limitations of these technologies, exploring their long-term effects, and evaluating their cost-effectiveness. To successfully implement them, a collaborative approach involving clinicians, researchers, engineers, and policymakers is necessary. This review provides an overview of current and future trends in emerging technologies for hand orthopedic surgery.

Literature Review of an Anterior Deprogrammer to Determine the Centric Relation and Presentation of Cases

The increasing demand for dental aesthetics, articulation corrections, and solutions for pain and frequent bruxism demands quick and effective restorative dental management. The biomedical research aimed to create a beneficial, ecological, and readily available anterior deprogrammer to determine the centric relation (CR) of cases. This medical device is additively manufactured from a biocompatible material. Size is customizable based on the width of the patient's anterior central incisors. This is a pilot study with two subjects. The task was to develop a complete data protocol for the production process, computer-aided design (CAD), and three-dimensional (3D) printing of the anterior deprogrammers. The research focused on creating simple and practically applicable tools for the dentist's prescription (anterior deprogrammer in three sizes), and secondly for the communication between the dentist and the patient (computer application). The tested hypothesis was whether, according to these novel tools, it is possible to produce functional occlusal splints, which could be manufactured using current technologies. This study compared a traditional splint with a digitally designed and 3D-printed one. The tested hypothesis was whether manufactured occlusal splints differ in patients' subjective perception of comfort. Each conservative treatment was monitored for ten weeks. Initial results are promising; no statistically significant difference was found between the productive technologies.

3D Printing of Individual Running Insoles - A Case Study

Purpose

The study's starting point is to find a low-cost and best-fit solution for comfortable movement for a recreational runner with knee pain using an orthopedic device. It is a case study. The research aims to apply digitization, CAD/CAM tools, and 3D printing to create an individual 3D running insole. The objective is to incorporate flexible shape optimization would provide comfort reductions in foot plantar pressures in one subject with knee pain while running. The test hypothesis was if it is possible to make it from one material. For this purpose, we created a new digital workflow based on the Decision Tree method and analyzed pain and comfort scores during user testing of prototypes.

Patient and Methods

The input data were obtained during a professional examination by a specialist doctor in the orthopedic outpatient clinic in the motion laboratory (DIERS 4D Motion Lab, Germany) with the output of data on the proband's complex movement stereotype. Surface and volumetric data were obtained in the biomedical laboratory with the 3D scanner. We modified the digital 3D foot models in 3D mesh software, developed the design in SW Gensole (Gyrobot, UK), and finally incorporated the internal structure and the surface layer of the insole data of the knowledge from the medical examination, comfort analyses, and scientific studies findings.

Results

Four complete 3D-printed prototypes (n=4) with differences in density and correction elements were designed. All of them were fabricated on a 3D printer (Prusa i3 MK3S, Czech Republic) with flexible TPU material suitable for skin contact. The Participant tested each of them five times in the field during a workout and final insoles three months on the routine training.

Conclusion

A novel workflow was created for designing, producing, and testing full 3D-printed insoles. The product is fit for immediate use.

Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment

This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients' treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently.

L. Shayeb M. Future of Orthodontics-A Systematic Review and Meta-Analysis on the Emerging Trends in This Field

Technology is rapidly evolving in the modern world, and the accompanying developments due to its influence are shaping each and every aspect of our life, with the field of orthodontics being no exception. This systematic review and meta-analysis aimed to examine such trends in orthodontics and hypothesize which ones would emerge and continue in the near future. After a thorough search of online journals using keywords such as "3D printing," "Aligners," "Artificial intelligence," "Future trends," "Orthodontics," and "Teleorthodontics" across databases of PubMed-MEDLINE, Web of Science, Cochrane, and Scopus, a total of 634 papers were initially recovered. Technological advancements in 3D printing, Computer-aided design and Computer-aided manufacturing (CAD/CAM), biopolymers and Teleorthodontics were the most important categories of development seen across the 17 studies that we selected for our review. All the investigations selected for this systematic review depicted aspects of orthodontics that were influenced by rapid technological changes and could potentially become mainstream in the coming times. However, caution was sought to be observed in the usage/adoption of some of these trends, with social media usage amongst both patients as well as orthodontists being a prime example of this.

Fabrication and In Vitro Characterization of Novel Hydroxyapatite Scaffolds 3D Printed Using Polyvinyl Alcohol as a Thermoplastic Binder

This paper presents a proof-of-concept study on the biocolonization of 3D-printed hydroxyapatite scaffolds with mesenchymal stem cells (MSCs). Three-dimensional (3D) printed biomimetic bone structure made of calcium deficient hydroxyapatite (CDHA) intended as a future bone graft was made from newly developed composite material for FDM printing. The biopolymer polyvinyl alcohol serves in this material as a thermoplastic binder for 3D molding of the printed object with a passive function and is completely removed during sintering. The study presents the material, the process of fused deposition modeling (FDM) of CDHA scaffolds, and its post-processing at three temperatures (1200, 1300, and 1400 °C), as well it evaluates the cytotoxicity and biocompatibility of scaffolds with MTT and LDH release assays after 14 days. The study also includes a morphological evaluation of cellular colonization with scanning electron microscopy (SEM) in two different filament orientations (rectilinear and gyroid). The results of the MTT assay showed that the tested material was not toxic, and cells were preserved in both orientations, with most cells present on the material fired at 1300 °C. Results of the LDH release assay showed a slight increase in LDH leakage from all samples. Visual evaluation of SEM confirmed the ideal post-processing temperature of the 3D-printed FDM framework for samples fired at 1300 °C and 1400 °C, with a porosity of 0.3 mm between filaments. In conclusion, the presented fabrication and colonization of CDHA scaffolds have great potential to be used in the tissue engineering of bones.

Smartphone-Based Facial Scanning as a Viable Tool for Facially Driven Orthodontics?

The current paradigm shift in orthodontic treatment planning is based on facially driven diagnostics. This requires an affordable, convenient, and non-invasive solution for face scanning. Therefore, utilization of smartphones' TrueDepth sensors is very tempting. TrueDepth refers to front-facing cameras with a dot projector in Apple devices that provide real-time depth data in addition to visual information. There are several applications that tout themselves as accurate solutions for 3D scanning of the face in dentistry. Their clinical accuracy has been uncertain. This study focuses on evaluating the accuracy of the Bellus3D Dental Pro app, which uses Apple's TrueDepth sensor. The app reconstructs a virtual, high-resolution version of the face, which is available for download as a 3D object. In this paper, sixty TrueDepth scans of the face were compared to sixty corresponding facial surfaces segmented from CBCT. Difference maps were created for each pair and evaluated in specific facial regions. The results confirmed statistically significant differences in some facial regions with amplitudes greater than 3 mm, suggesting that current technology has limited applicability for clinical use. The clinical utilization of facial scanning for orthodontic evaluation, which does not require accuracy in the lip region below 3 mm, can be considered.

Artificial Intelligence Applications in Health Care Practice: Scoping Review

BACKGROUND

Artificial intelligence (AI) is often heralded as a potential disruptor that will transform the practice of medicine. The amount of data collected and available in health care, coupled with advances in computational power, has contributed to advances in AI and an exponential growth of publications. However, the development of AI applications does not guarantee their adoption into routine practice. There is a risk that despite the resources invested, benefits for patients, staff, and society will not be realized if AI implementation is not better understood.

OBJECTIVE

The aim of this study was to explore how the implementation of AI in health care practice has been described and researched in the literature by answering 3 questions: What are the characteristics of research on implementation of AI in practice? What types and applications of AI systems are described? What characteristics of the implementation process for AI systems are discernible?

METHODS

A scoping review was conducted of MEDLINE (PubMed), Scopus, Web of Science, CINAHL, and PsycINFO databases to identify empirical studies of AI implementation in health care since 2011, in addition to snowball sampling of selected reference lists. Using Rayyan software, we screened titles and abstracts and selected full-text articles. Data from the included articles were charted and summarized.

RESULTS

Of the 9218 records retrieved, 45 (0.49%) articles were included. The articles cover diverse clinical settings and disciplines; most (32/45, 71%) were published recently, were from high-income countries (33/45, 73%), and were intended for care providers (25/45, 56%). AI systems are predominantly intended for clinical care, particularly clinical care pertaining to patient-provider encounters. More than half (24/45, 53%) possess no action autonomy but rather support human decision-making. The focus of most research was on establishing the effectiveness of interventions (16/45, 35%) or related to technical and computational aspects of AI systems (11/45, 24%). Focus on the specifics of implementation processes does not yet seem to be a priority in research, and the use of frameworks to guide implementation is rare.

CONCLUSIONS

Our current empirical knowledge derives from implementations of AI systems with low action autonomy and approaches common to implementations of other types of information systems. To develop a specific and empirically based implementation framework, further research is needed on the more disruptive types of AI systems being implemented in routine care and on aspects unique to AI implementation in health care, such as building trust, addressing transparency issues, developing explainable and interpretable solutions, and addressing ethical concerns around privacy and data protection.

Pierre Robin Sequence and 3D Printed Personalized Composite Appliances in Interdisciplinary Approach

This paper introduces a complex novel concept and methodology for the creation of personalized biomedical appliances 3D-printed from certified biocompatible photopolymer resin Dental LT Clear (V2). The explained workflow includes intraoral and CT scanning, patient virtualization, digital appliance design, additive manufacturing, and clinical application with evaluation of the appliance intended for patients with cranio-facial syndromes. The presented concept defines virtual 3D fusion of intraoral optical scan and segmented CT as sufficient and accurate data defining the 3D surface of the face, intraoral and airway morphology necessary for the 3D design of complex personalized intraoral and extraoral parts of the orthopedic appliance. A central aspect of the concept is a feasible utilization of composite resin for biomedical prototyping of the sequence of marginally different appliances necessary to keep the pace with the patient rapid growth. Affordability, noninvasiveness, and practicality of the appliance update process shall be highlighted. The methodology is demonstrated on a particular case of two-year-old infant with Pierre Robin sequence. Materialization by additive manufacturing of this photopolymer provides a highly durable and resistant-to-fracture two-part appliance similar to a Tübingen palatal plate, for example. The paper concludes with the viability of the described method and material upon interdisciplinary clinical evaluation of experts from departments of orthodontics and cleft anomalies, pediatric pneumology and phthisiology, and pediatric otorhinolaryngology.

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

Dental Care and Education Facing Highly Transmissible SARS-CoV-2 Variants: Prospective Biosafety Setting: Prospective, Single-Arm, Single-Center Study

With the arrival of the highly transmissible Omicron variants (BA.4 and BA.5), dentistry faces another seasonal challenge to preserve the biosafety of dental care and education. With the aim of protecting patients, students, teachers and healthcare professionals, this paper introduces a prospective sustainable biosafety setting for everyday dental care and education. The setting developed by dental clinicians, epidemiologists, and teachers of dentistry consists of a combination of modern technologies focused on the air-borne part of the viral pathway. The introduced biosafety setting has been clinically evaluated after 18 months of application in the real clinical environment. The protocol has three fundamental pillars: (1) UVC air disinfection; (2) air saturation with certified virucidal essences with nebulizing diffusers; (3) complementary solutions including telehealth and 3D printing. A pseudonymous online smart form was used as the evaluation method. The protocol operates on the premise that everybody is a hypothetical asymptomatic carrier. The results of a clinical evaluation of 115 patient feedbacks imply that no virus transmission from patient to patient or from doctor to nurse was observed or reported using this protocol, and vice versa, although nine patients retrospectively admitted that the clinic visit is likely to be infectious. Despite these promising results, a larger clinical sample and exposition to the current mutated strains are needed for reliable conclusions about protocol virucidal efficiency in current dental environments.

Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact

(1) Teeth, in humans, represent the most resilient tissues. However, exposure to concentrated acids might lead to their dissolving, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper aims to introduce a novel method for the 3D reconstruction of dental patterns as a crucial step for the digital identification of dental records. (2) With a combination of modern methods, including micro-computed tomography, cone-beam computer tomography, and attenuated total reflection, in conjunction with Fourier transform infrared spectroscopy and artificial intelligence convolutional neural network algorithms, this paper presents a method for 3D-dental-pattern reconstruction, and human remains identification. Our research studies the morphology of teeth, bone, and dental materials (amalgam, composite, glass-ionomer cement) under different periods of exposure to 75% sulfuric acid. (3) Our results reveal a significant volume loss in bone, enamel, dentine, as well as glass-ionomer cement. The results also reveal a significant resistance by the composite and amalgam dental materials to the impact of sulfuric acid, thus serving as strong parts in the dental-pattern mosaic. This paper also probably introduces the first successful artificial intelligence application in automated-forensic-CBCT segmentation. (4) Interdisciplinary cooperation, utilizing the mentioned technologies, can solve the problem of human remains identification with a 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

Utility of Teleorthodontics in Orthodontic Emergencies during the COVID-19 Pandemic: A Systematic Review

Background. Coronavirus disease has subjected the whole of humanity to two years of social isolation and a series of restrictions. These circumstances have led to the use of information technology in an increasingly widespread manner. Even in the dental field, telematic means have been used to respond to emergencies. The aim of this systematic review of the literature is to evaluate the types of orthodontic emergency that occurred most often and how they were managed by teleorthodontics during the COVID-19 pandemic. The secondary aim is that clinicians will use teleorthodontics not only during pandemics but as an additional tool to manage orthodontics. Materials and Methods. Out of 1695 articles available on PubMed, Science Direct, Cochrane and SciELO, eight articles were selected for this systematic literature review. Google Scholar was used as a secondary source to confirm that there were no additional articles. The screened papers comprised editorials, clinical studies, cross-sectional studies and retrospective studies in Italian, English or Spanish language. Results. The articles showed that the means by which patients most often communicated with their orthodontists were voice calls and smartphone applications such as WhatsApp^® Messenger. Through these media, patients communicated their orthodontic emergencies. These mainly involved fixed multibracket appliances and the most common issues were discomfort and pain, fracture or loss of the appliance, protruding distal ends of archwires, brackets, tubes and bands or retainer detachment. Through teleorthodontics, patients could solve these issues by using orthodontic relief wax, cutting the protruding distal ends of the archwire with a nail clipper or a stronger cutter and removing or replacing detached bands, brackets, tubes or metallic ligature with a clean tweezer. Conclusions. In situations where personal contact is limited, teleorthodontics represents a valuable aid for professionals and patients facing orthodontic emergencies. The hope is that it may continue to represent a valuable aid for patients with difficulties in planning an in-office visit.

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

The problem of computerising the design and development of 3D-printed chainmail with programmed directional functions provides a basis for further research, including the automation of medical devices. The scope of the present research was focused on computational optimisation of the selection of materials and shapes for 3D printing, including the design of medical devices, which constitutes a significant scientific, technical, and clinical problem. The aim of this article was to solve the scientific problem of automated or semi-automated efficient and practical design of 3D-printed chainmail with programmed directional functions (variable stiffness/elasticity depending on the direction). We demonstrate for the first time that 3D-printed particles can be arranged into single-layer chainmail with a tunable one- or two-directional bending modulus for use in a medical hand exoskeleton. In the present work, we accomplished this in two ways: based on traditional programming and based on machine learning. This paper presents the novel results of our research, including 3D printouts, providing routes toward the wider implementation of adaptive chainmails. Our research resulted in an automated or semi-automated efficient and practical 3D printed chainmail design with programmed directional functions for a wrist exoskeleton with variable stiffness/flexibility, depending on the direction. We also compared two methodologies of planning and construction: the use of traditional software and machine-learning-based software, with the latter being more efficient for more complex chainmail designs.

Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia in Young People: Preliminary Findings from Systematic Review and Meta-Analysis

Various forms of cognitive behavioral therapy for insomnia (CBT-i) have been developed to improve its scalability and accessibility for insomnia management in young people, but the efficacy of digitally-delivered cognitive behavioral therapy for insomnia (dCBT-i) remains uncertain. This study systematically reviewed and evaluated the effectiveness of dCBT-i among young individuals with insomnia. We conducted comprehensive searches using four electronic databases (PubMed, Cochrane Library, PsycINFO, and Embase; until October 2021) and examined eligible records. The search strategy comprised the following three main concepts: (1) participants were adolescents or active college students; (2) dCBT-I was employed; (3) standardized tools were used for outcome measurement. Four randomized controlled trials qualified for meta-analysis. A significant improvement in self-reported sleep quality with a medium-to-large effect size after treatment (Hedges’s g = −0.58~−0.80) was noted. However, a limited effect was detected regarding objective sleep quality improvement (total sleep time and sleep efficiency measured using actigraphy). These preliminary findings from the meta-analysis suggest that dCBT-i is a moderately effective treatment in managing insomnia in younger age groups, and CBT-i delivered through the web or a mobile application is an acceptable approach for promoting sleep health in young people.

Predicting Interest in Orthodontic Aligners: A Google Trends Data Analysis

Aligners are an example of how advances in dentistry can develop from innovative combinations of 3D technologies in imaging, planning and printing to provide new treatment modalities. With increasing demand for esthetic orthodontic treatment, aligners have grown in popularity because they are esthetically more pleasing and less obstructive to oral hygiene and other oral functions compared to fixed orthodontic appliances. To observe and estimate aligner treatment interest among Google Search users, Google Trends data were obtained and analyzed for the search term, "Invisalign". A prediction of interest for the year 2022 for three European Union countries with the highest GDP was developed. "Invisalign" was chosen to represent all orthodontic aligners as the most searched term in Google Trends for aligners. This is the first study to predict interest in the query "Invisalign" in a Google search engine. The Prophet algorithm, which depends on advanced statistical analysis methods, positions itself as an automatic prediction procedure and was used to predict Google Trends data. Seasonality modeling was based on the standard Fourier series to provide a flexible model of periodic effects. The results predict an increase in "Invisalign" in Google Trends queries in the coming year, increasing by around 6%, 9% and 13% by the end of 2022 compared to 2021 for France, Italy and Germany, respectively. Forecasting allows practitioners to plan for growing demand for particular treatments, consider taking continuing education, specifically, aligner certification courses, or introduce modern scanning technology into offices. The oral health community can use similar prediction tools and methods to remain alert to future changes in patient demand to improve the responses of professional organizations as a whole, work more effectively with governments if needed, and provide better coordination of care for patients.