Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues

Dental photography for children: A global survey

BACKGROUND

Clinical photographs are now considered an essential element for accurate and objective dental records. Very little information exists on dental photography in children and the factors that can influence the dentist's decision to take dental photographs.

AIM

This study aimed to assess the current use, attitude and confidence of paediatric dentists using clinical dental photography of children worldwide.

DESIGN

This was a cross-sectional questionnaire-based study distributed online to paediatric dentists around the globe.

RESULTS

The survey was completed by 390 dentists. The majority of participants (82.3%, n = 321) took dental photographs of their patients, and over 74% of the participants were confident in taking dental photographs. Sixty-nine dentists (17.7%) did not take photographs. Seventy-four per cent (n = 240) of those who take dental photographs and 47.8% (n = 33) of those who do not take dental photographs reported an effect on the child's behaviour. The majority of participants expressed interest in receiving further training.

CONCLUSION

Most paediatric dentists take dental photographs of their patients and value their role in the behavioural management of the child patient. Paediatric dentists need further training in children's dental photography, including guidance on proper image recording, storage and transfer.

Level of implementation of digital transformation in dental radiology centers in Metropolitan Lima: A cross-sectional study

Background

Digital transformation (DT) involves introducing digital technologies into business models in all areas. This research aimed to evaluate the level of implementation of DT using the digital health indicator in private radiology centers in Lima, Perú.

Material and Methods

Forty-five randomly selected radiology centers included in a database of 50 registered centers were evaluated. The inclusion criteria were having a web domain and institutional email address. They were digitally surveyed using a digital survey (HIMSS DHI Rapid) measuring four dimensions: interoperability, governance and workforce, predictive analytics, and person-enabled health. These indicators allowed determination of the digital transformation level of a radiological company. The level of implementation was measured quantitatively on a scale from 0 to 400, and the Kruskal Wallis test (p>0.05) was used to compare DT according to the geographical location of the centers.

Results

The digital health indicator obtained was 60.24 ± 43.14 out of 400 achievable points. The dimensional analysis in terms of interoperability was 24 ± 18.09, followed by governance and workforce at 23.44 ± 18.58, person-enabled health at 18.73 ± 15.63, and finally, predictive analysis at 16.18 ± 13.51. No significant differences were found in health indicator dimensions according to the geographical location (p>0.05).

Conclusions

DT in maxillofacial radiology centers in Lima is at an initial level. Radiology centers should take this situation into account to have relevant information for making diagnostic and treatment decisions and to provide better preventive health policies to benefit the population. Key words:Digital transformation, digital health indicator, dental radiology.

Perceptions in Digital Smile Design: Assessing Laypeople and Dental Professionals' Preferences Using an Artificial-Intelligence-Based Application

Digital Smile Design (DSD) is used in many fields of dentistry. This prospective observational study assessed laypeople's and dental professionals' perceptions of a DSD application. SmileCloud, an online DSD platform, was used to create two different designs for three patients; after that, the participants, in a 30-question online illustrated survey, were asked about the most attractive design and other features of the smile. Dentists' and laypeople's perceptions about specific DSD features were assessed. The Kolmogorov-Smirnov normality test was used. Descriptive and crosstab analyses compared the respondents' opinions for each statement. Chi-square tests were used to determine the relationship between the questions and any association with age, gender, and profession. The test results were rated as significant at a p-value < 0.05. A total of 520 participants (dental professionals, students, dental technicians, and laypeople) were enrolled. The statistically significant features were self-esteem related to appearance (p = 0.05), facial and smile symmetry (p = 0.42, p < 0.0001), tooth color (p = 0.012), and symmetry of gums (p < 0.001). For each patient, the design with dominant round upper incisors and perfect symmetry was preferred (p < 0.001). Digital pre-visualization benefits diagnosis and enriches treatment planning. The dentist-dental technician-patient team should be involved in the decision-making process of pre-visualization.

OII-DS: A benchmark Oral Implant Image Dataset for object detection and image classification evaluation

In recent years, there is been a growing reliance on image analysis methods to bolster dentistry practices, such as image classification, segmentation and object detection. However, the availability of related benchmark datasets remains limited. Hence, we spent six years to prepare and test a bench Oral Implant Image Dataset (OII-DS) to support the work in this research domain. OII-DS is a benchmark oral image dataset consisting of 3834 oral CT imaging images and 15240 oral implant images. It serves the purpose of object detection and image classification. To demonstrate the validity of the OII-DS, for each function, the most representative algorithms and metrics are selected for testing and evaluation. For object detection, five object detection algorithms are adopted to test and four evaluation criteria are used to assess the detection of each of the five objects. Additionally, mean average precision serves as the evaluation metric for multi-objective detection. For image classification, 13 classifiers are used for testing and evaluating each of the five categories by meeting four evaluation criteria. Experimental results affirm the high quality of our data in OII-DS, rendering it suitable for evaluating object detection and image classification methods. Furthermore, OII-DS is openly available at the URL for non-commercial purpose: https://doi.org/10.6084/m9.figshare.22608790.

Revolutionising dental technologies: a qualitative study on dental technicians' perceptions of Artificial intelligence integration

BACKGROUND

The integration of artificial intelligence (AI) in dentistry has the potential to revolutionise the field of dental technologies. However, dental technicians' views on the use of AI in dental technology are still sparse in the literature. This qualitative study aimed to explore the perceptions of dental technicians regarding the use of AI in their dental laboratory practice.

METHODS

Twelve dental technicians with at least five years of professional experience and currently working in Malaysia agreed to participate in the one-to-one in-depth online interviews. Interviews were recorded, transcribed verbatim and translated. Thematic analysis was conducted to identify patterns, themes, and categories within the interview transcripts.

RESULTS

The analysis revealed two key themes: "Perceived Benefits of AI" and "Concerns and Challenges". Dental technicians recognised the enhanced efficiency, productivity, accuracy, and precision that AI can bring to dental laboratories. They also acknowledged the streamlined workflow and improved communication facilitated by AI systems. However, concerns were raised regarding job security, professional identity, ethical considerations, and the need for adequate training and support.

CONCLUSION

This research sheds light on the potential benefits and challenges associated with the integration of AI in dental laboratory practices. Understanding these perceptions and addressing the challenges can support the effective integration of AI in dental laboratories and contribute to the growing body of literature on AI in healthcare.

Cognitive Web Service-Based Learning Analytics in Education Systems Using Big Data Analytics

In the field of education, digital learning plays an important part. For each passing day, digital learning is displacing the traditional method of education. An accurate analysis of a student's qualities improves their academic performance. With the advancement of technology and big data, there are many applications for big data analytics, including education. Huge volumes of academic information are being generated, and discovering a technique to harness and analyze this information effectively is a challenging issue among many educational organizations. In this paper, educational clustering big data mining system (ECBDMS) has been proposed. The cognitive web service based learning analytic(CWS-LA) system is integrated to securely categorize and provide ease of access to the data. ECBDMS has been found to improve performance gains of 92.8%, prediction ratios of 88.6%, clustering error ratios of 2.3 percent, learning percentages of 94%, and forecasting accuracy of 97.1 percent when compared to other existing methods.

Investigating pregnant women’s health information needs during pregnancy on internet platforms

Artificial intelligence gives pregnant women another avenue for receiving healthcare information. With the advancement of information and communication technology, searching online for pregnancy information has become commonplace during COVID-19. This study aimed to explore pregnant women’s information-seeking behavior based on data mining and text analysis in China. Posts on maternal and infant-related websites were collected during 1 June 2020, and 31 January 2021. A total of 5,53,117 valid posts were obtained. Based on the data, we performed correlation analysis, topic analysis, and sentiment analysis. The correlation analysis showed the positive effects of population, population with a college education or above, and GDP on post counts. The topic analysis extracted six, nineteen, eighteen, thirteen, eleven, sixteen, thirteen, sixteen, nineteen, and fourteen topics in different months of pregnancy, reflecting different information needs in various pregnancy periods. The results of sentiment analysis show that a peak of the posts emerged in the second month of pregnancy and the proportion of emotionally positive posts reached its peak in the sixth month of pregnancy. The study provides important insights for understanding pregnant women’s information-seeking behavior.

Effect of decompression and online transmission on the dimensional changes of .stl files generated by intra-oral scanning

Intraoral scans became part of the virtual planning in Dentistry. In the new scenario of digital workflows, dental clinics and laboratories had to establish an online communication that requires the compression, decompression, and transmission of 3D files. Knowledge about the effects of these procedures on the dimensional properties of the files is fundamental to ensure a more realistic virtual planning. The aim of this study was to assess the influence of 3D file compression, decompression, and online transmission on the dimensional properties of dental models from intraoral scanning. Intraoral scan files in.stl format of 50 patients were selected from the database of a dental radiology clinic, with 25 of these patients with mixed dentition and 25 with permanent dentition. The maxilla and mandible scans of each patient were included in the study, generating a total of 100 files. A folder with the 100 files was created and replicated six times with different labels (A, B, C, D, E, F), totaling a sample number of 600 files. Folder A was compressed by WinZip and then decompressed. Folder B went through the same process, but the step of compression and decompression by WinZip was repeated 10 times. The folders C, D, E, F were sent, respectively, through the platforms WeTransfer, Dropbox, Google Drive, and OneDrive, then each of them was downloaded in their respective platforms. After the six folders went through the compression process and were sent by the platforms, each file in the folder was compared with its original file by superimposing the 3D images and identifying the dimensional deviation in the compressed file in relation to the original file. We observed that there were no differences between the six groups regarding dimensional changes from the compression, decompression and online transmission processes. The lack of dimensional changes was observed for the sets of permanent and deciduous. teeth We concluded that it is possible to compress, decompress, and transfer.stl format files online without causing dimensional distortions in the 3D model.

Smartphone technology for communications between clinicians - A scoping review

OBJECTIVES

This scoping review aims to review explore, assess, and map the literature to inform clinical practice regarding communication between clinicians. Specific Apps/channels used were identified and assessed with a focus on data security with key concepts and knowledge gaps identified.

DATA

The Joanna Briggs Institute framework is followed, with search results reported as per the PRISMA ScR for scoping reviews guidelines.

SOURCES

A systematic search strategy encompassing EBSCO and OneSearch databases was conducted - two identical searches, (June and October 2020) limited to English language articles published 2016-2020. A narrative synthesis was used to integrate and report the findings.

STUDY SELECTION

Sixty-six publications were selected. Twelve from EBSCO, thirty-five from OneSearch, nineteen were hand searched. Sixteen of the publications were research studies, nine were literature reviews, twenty-six were editorial, one was a newspaper article and fourteen were grey literature. Instant Messaging (40%, n = 23), image sharing (41%, n = 24), and video conferencing (19%, n = 11) were functions most popular with clinicians. WhatsApp, generic instant messaging, Facebook messenger, ZOOM, and Skype are evidenced as channels for communication between clinicians within the EU. A sizeable proportion of the publications (38%; n = 25) failed to identify or adequately address technical security concerns and requirements around privacy and data protection.

CONCLUSIONS

Clinicians use smartphones /Apps to communicate clinical information with each other. The security and privacy issues arising from their communication of sensitive data is absent or only superficially acknowledged within the literature.

CLINICAL SIGNIFICANCE

Clinician's need clearer guidance on the use of smartphone technology for clinical communications.

Personalized workflows in reconstructive dentistry-current possibilities and future opportunities

OBJECTIVES

The increasing collection of health data coupled with continuous IT advances have enabled precision medicine with personalized workflows. Traditionally, dentistry has lagged behind general medicine in the integration of new technologies: So what is the status quo of precision dentistry? The primary focus of this review is to provide a current overview of personalized workflows in the discipline of reconstructive dentistry (prosthodontics) and to highlight the disruptive potential of novel technologies for dentistry; the possible impact on society is also critically discussed.

MATERIAL AND METHODS

Narrative literature review.

RESULTS

Narrative literature review.

CONCLUSIONS

In the near future, artificial intelligence (AI) will increase diagnostic accuracy, simplify treatment planning, and thus contribute to the development of personalized reconstructive workflows by analyzing e-health data to promote decision-making on an individual patient basis. Dental education will also benefit from AI systems for personalized curricula considering the individual students' skills. Augmented reality (AR) will facilitate communication with patients and improve clinical workflows through the use of visually guided protocols. Tele-dentistry will enable opportunities for remote contact among dental professionals and facilitate remote patient consultations and post-treatment follow-up using digital devices. Finally, a personalized digital dental passport encoded using blockchain technology could enable prosthetic rehabilitation using 3D-printed dental biomaterials.

CLINICAL SIGNIFICANCE

Overall, AI can be seen as the door-opener and driving force for the evolution from evidence-based prosthodontics to personalized reconstructive dentistry encompassing a synoptic approach with prosthetic and implant workflows. Nevertheless, ethical concerns need to be solved and international guidelines for data management and computing power must be established prior to a widespread routine implementation.

Augmented, Virtual and Mixed Reality in Dentistry: A Narrative Review on the Existing Platforms and Future Challenges

The recent advancements in digital technologies have led to exponential progress in dentistry. This narrative review aims to summarize the applications of Augmented Reality, Virtual Reality and Mixed Reality in dentistry and describes future challenges in digitalization, such as Artificial Intelligence and Robotics. Augmented Reality, Virtual Reality and Mixed Reality represent effective tools in the educational technology, as they can enhance students’ learning and clinical training. Augmented Reality and Virtual Reality and can also be useful aids during clinical practice. Augmented Reality can be used to add digital data to real life clinical data. Clinicians can apply Virtual Reality for a digital wax-up that provides a pre-visualization of the final post treatment result. In addition, both these technologies may also be employed to eradicate dental phobia in patients and further enhance patient’s education. Similarly, they can be used to enhance communication between the dentist, patient, and technician. Artificial Intelligence and Robotics can also improve clinical practice. Artificial Intelligence is currently developed to improve dental diagnosis and provide more precise prognoses of dental diseases, whereas Robotics may be used to assist in daily practice.

Computational healthcare: Present and future perspectives (Review)

Artificial intelligence (AI) has been developed through repeated new discoveries since around 1960. The use of AI is now becoming widespread within society and our daily lives. AI is also being introduced into healthcare, such as medicine and drug development; however, it is currently biased towards specific domains. The present review traces the history of the development of various AI-based applications in healthcare and compares AI-based healthcare with conventional healthcare to show the future prospects for this type of care. Knowledge of the past and present development of AI-based applications would be useful for the future utilization of novel AI approaches in healthcare.

Artificial Intelligence and Ethics in Dentistry: A Scoping Review

Dentistry increasingly integrates artificial intelligence (AI) to help improve the current state of clinical dental practice. However, this revolutionary technological field raises various complex ethical challenges. The objective of this systematic scoping review is to document the current uses of AI in dentistry and the ethical concerns or challenges they imply. Three health care databases (MEDLINE [PubMed], SciVerse Scopus, and Cochrane Library) and 2 computer science databases (ArXiv, IEEE Xplore) were searched. After identifying 1,553 records, the documents were filtered, and a full-text screening was performed. In total, 178 studies were retained and analyzed by 8 researchers specialized in dentistry, AI, and ethics. The team used Covidence for data extraction and Dedoose for the identification of ethics-related information. PRISMA guidelines were followed. Among the included studies, 130 (73.0%) studies were published after 2016, and 93 (52.2%) were published in journals specialized in computer sciences. The technologies used were neural learning techniques for 75 (42.1%), traditional learning techniques for 76 (42.7%), or a combination of several technologies for 20 (11.2%). Overall, 7 countries contributed to 109 (61.2%) studies. A total of 53 different applications of AI in dentistry were identified, involving most dental specialties. The use of initial data sets for internal validation was reported in 152 (85.4%) studies. Forty-five ethical issues (related to the use AI in dentistry) were reported in 22 (12.4%) studies around 6 principles: prudence (10 times), equity (8), privacy (8), responsibility (6), democratic participation (4), and solidarity (4). The ratio of studies mentioning AI-related ethical issues has remained similar in the past years, showing that there is no increasing interest in the field of dentistry on this topic. This study confirms the growing presence of AI in dentistry and highlights a current lack of information on the ethical challenges surrounding its use. In addition, the scarcity of studies sharing their code could prevent future replications. The authors formulate recommendations to contribute to a more responsible use of AI technologies in dentistry.

Clinical decision support systems in orthodontics: A narrative review of data science approaches

Advancements in technology and data collection generated immense amounts of information from various sources such as health records, clinical examination, imaging, medical devices, as well as experimental and biological data. Proper management and analysis of these data via high-end computing solutions, artificial intelligence and machine learning approaches can assist in extracting meaningful information that enhances population health and well-being. Furthermore, the extracted knowledge can provide new avenues for modern healthcare delivery via clinical decision support systems. This manuscript presents a narrative review of data science approaches for clinical decision support systems in orthodontics. We describe the fundamental components of data science approaches including (a) Data collection, storage and management; (b) Data processing; (c) In-depth data analysis; and (d) Data communication. Then, we introduce a web-based data management platform, the Data Storage for Computation and Integration, for temporomandibular joint and dental clinical decision support systems.

The effects of images posted to social media by orthodontists on public perception of professional credibility and willingness to become a client

BACKGROUND

Many patients choose health professionals using the Internet, whether through websites or social media. In orthodontics, an orthodontist's relationship with active and potential patients can be affected by social media interactions, both as a marketing tool and as a tool for providing educational information. The purpose of the present study was to analyze the public perception of professional credibility and willingness to become a client, based on images posted by orthodontists on Instagram.

METHOD

This was a cross-sectional study performed using a digital self-administered questionnaire based on images from public Instagram profiles of orthodontists found using certain hashtags. The themes of the posts were analyzed through a qualitative analysis, and the results were expressed as categories. After analyzing 2445 images, 12 thematic categories emerged. A total of 446 individuals (225 laypeople, 66 dental students, and 155 dentists) evaluated the images in regard to the perception of professional credibility and willingness to become a client. One-way ANOVA and chi-square tests were applied, considering a 5% significance level.

RESULTS

It was found that more than 95% of the participants used social media, primarily Instagram, WhatsApp, and Facebook, and the social network most used to research health services was Instagram. Statistically significant differences were found in the mean value of perceived professional credibility between the groups (p < 0.05) for the following categories: "dental traction," "mini-implant mechanics," "before and after treatment," "aesthetic brackets," "metallic brackets," and "clear aligners." The categories "being a teacher" and "before and after treatment" had a higher impact on the participants' perception of credibility and willingness to become a client, unlike the "social relationship" and "family relationship" categories.

CONCLUSIONS

Some of the themes found in the orthodontists' social media posts were found to influence the perceptions around professional credibility and willingness to become a client, although there were differences among the participants in the present study.

The Modern and Digital Transformation of Oral Health Care: A Mini Review

Dentistry is a part of the field of medicine which is advocated in this digital revolution. The increasing trend in dentistry digitalization has led to the advancement in computer-derived data processing and manufacturing. This progress has been exponentially supported by the Internet of medical things (IoMT), big data and analytical algorithm, internet and communication technologies (ICT) including digital social media, augmented and virtual reality (AR and VR), and artificial intelligence (AI). The interplay between these sophisticated digital aspects has dramatically changed the healthcare and biomedical sectors, especially for dentistry. This myriad of applications of technologies will not only be able to streamline oral health care, facilitate workflow, increase oral health at a fraction of the current conventional cost, relieve dentist and dental auxiliary staff from routine and laborious tasks, but also ignite participatory in personalized oral health care. This narrative article review highlights recent dentistry digitalization encompassing technological advancement, limitations, challenges, and conceptual theoretical modern approaches in oral health prevention and care, particularly in ensuring the quality, efficiency, and strategic dental care in the modern era of dentistry.

Dental 3D-Printing: Transferring Art from the Laboratories to the Clinics

The rise of three-dimensional (3D) printing technology has changed the face of dentistry over the past decade. 3D printing is a versatile technique that allows the fabrication of fully automated, tailor-made treatment plans, thereby delivering personalized dental devices and aids to the patients. It is highly efficient, reproducible, and provides fast and accurate results in an affordable manner. With persistent efforts among dentists for refining their practice, dental clinics are now acclimatizing from conventional treatment methods to a fully digital workflow to treat their patients. Apart from its clinical success, 3D printing techniques are now employed in developing haptic simulators, precise models for dental education, including patient awareness. In this narrative review, we discuss the evolution and current trends in 3D printing applications among various areas of dentistry. We aim to focus on the process of the digital workflow used in the clinical diagnosis of different dental conditions and how they are transferred from laboratories to clinics. A brief outlook on the most recent manufacturing methods of 3D printed objects and their current and future implications are also discussed.