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Big Data in Dental Research and Oral Healthcare
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Big Data in Dental Research and Oral Healthcare

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (15 November 2020) | Viewed by 46054

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Tim Joda

E-Mail Website
Guest Editor
Head of eHealth in Reconstructive Dentistry, Clinic of Reconstructive Dentistry, Center for Dental Medicine, University of Zurich, 8006 Zürich, Switzerland
Interests: reconstructive dentistry; prosthodontics; implant dentistry; digital technology; dental materials; augmented/virtual reality; artificial intelligence; big data & eHealth; public health; translational research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advances in information technology have fostered a global explosion of data generation. Accumulated big data is now estimated to be 4.4 zettabytes in the digital universe; and trends predict an exponential increase in the future. Health data is gathered from professional routine care and other expanded sources including the social determinants of health, such as internet of things.

Biomedical research has recently moved through three stages in digital healthcare: (1) data collection; (2) data sharing; and (3) data analytics. With the explosion of stored health data, dental medicine is edging into its fourth stage of digitization using new technologies including augmented & virtual reality, artificial intelligence, and blockchain.

Big data collaborations involve interactions between a diverse range of stakeholders with analytical, technical and political focus. In oral healthcare, data technology has many areas of application: prognostic analysis and predictive modeling, identification of unknown correlations of diseases, clinical decision support for novel treatment concepts, public health surveys and population-based clinical research, as well as the evaluation of healthcare systems.

The objective of this Special Issue is to provide an update on the current knowledge with state-of-the-art theory and practical information on human and social perspectives that determine the uptake of technological innovations in big data science in the field of dental medicine. Moreover, it will focus on the identification of future research needs to manage the continuous increase of health data and to accomplish its clinical translation for patient-centered research and personalized dentistry.

This Special Issue welcomes all types of studies and reviews considering the perspectives of different stakeholders on technological innovations for big data science in all dental disciplines.

Prof. Dr. Tim Joda, DMD, MSc, PhD
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Dentistry
  • Oral Healthcare
  • Dental Research
  • Big Data
  • Public Health
  • Personalized Medicine
  • Augmented / Virtual Reality [AR/VR]
  • Artificial Intelligence [AI]
  • Blockchain

Published Papers (7 papers)

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Research

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11 pages, 4218 KiB  
Article
Does Last Year’s Cost Predict the Present Cost? An Application of Machine Leaning for the Japanese Area-Basis Public Health Insurance Database
by Yoshiaki Nomura, Yoshimasa Ishii, Yota Chiba, Shunsuke Suzuki, Akira Suzuki, Senichi Suzuki, Kenji Morita, Joji Tanabe, Koji Yamakawa, Yasuo Ishiwata, Meu Ishikawa, Kaoru Sogabe, Erika Kakuta, Ayako Okada, Ryoko Otsuka and Nobuhiro Hanada
Int. J. Environ. Res. Public Health 2021, 18(2), 565; https://doi.org/10.3390/ijerph18020565 - 12 Jan 2021
Cited by 6 | Viewed by 2367
Abstract
The increasing healthcare cost imposes a large economic burden for the Japanese government. Predicting the healthcare cost may be a useful tool for policy making. A database of the area-basis public health insurance of one city was analyzed to predict the medical healthcare [...] Read more.
The increasing healthcare cost imposes a large economic burden for the Japanese government. Predicting the healthcare cost may be a useful tool for policy making. A database of the area-basis public health insurance of one city was analyzed to predict the medical healthcare cost by the dental healthcare cost with a machine learning strategy. The 30,340 subjects who had continued registration of the area-basis public health insurance of Ebina city during April 2017 to September 2018 were analyzed. The sum of the healthcare cost was JPY 13,548,831,930. The per capita healthcare cost was JPY 446,567. The proportion of medical healthcare cost, medication cost, and dental healthcare cost was 78%, 15%, and 7%, respectively. By the results of the neural network model, the medical healthcare cost proportionally depended on the medical healthcare cost of the previous year. The dental healthcare cost of the previous year had a reducing effect on the medical healthcare cost. However, the effect was very small. Oral health may be a risk for chronic diseases. However, when evaluated by the healthcare cost, its effect was very small during the observation period. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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13 pages, 1393 KiB  
Article
Dental Practice Integration into Primary Care: A Microsimulation of Financial Implications for Practices
by Sung Eun Choi, Lisa Simon, Jane R. Barrow, Nathan Palmer, Sanjay Basu and Russell S. Phillips
Int. J. Environ. Res. Public Health 2020, 17(6), 2154; https://doi.org/10.3390/ijerph17062154 - 24 Mar 2020
Cited by 4 | Viewed by 3095
Abstract
Given the widespread lack of access to dental care for many vulnerable Americans, there is a growing realization that integrating dental and primary care may provide comprehensive care. We sought to model the financial impact of integrating dental care provision into a primary [...] Read more.
Given the widespread lack of access to dental care for many vulnerable Americans, there is a growing realization that integrating dental and primary care may provide comprehensive care. We sought to model the financial impact of integrating dental care provision into a primary care practice. A microsimulation model was used to estimate changes in net revenue per practice by simulating patient visits to a primary dental practice within primary care practices, utilizing national survey and un-identified claims data from a nationwide health insurance plan. The impact of potential changes in utilization rates and payer distributions and hiring additional staff was also evaluated. When dental care services were provided in the primary care setting, annual net revenue changes per practice were −$92,053 (95% CI: −93,054, −91,052) in the first year and $104,626 (95% CI: 103,315, 105,316) in subsequent years. Net revenue per annum after the first year of integration remained positive as long as the overall utilization rates decreased by less than 25%. In settings with a high proportion of publicly insured patients, the net revenue change decreased but was still positive. Integrating primary dental and primary care providers would be financially viable, but this viability depends on demands of dental utilization and payer distributions. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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Review

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18 pages, 654 KiB  
Review
Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice
by Kuofeng Hung, Andy Wai Kan Yeung, Ray Tanaka and Michael M. Bornstein
Int. J. Environ. Res. Public Health 2020, 17(12), 4424; https://doi.org/10.3390/ijerph17124424 - 19 Jun 2020
Cited by 54 | Viewed by 8345
Abstract
The increasing use of three-dimensional (3D) imaging techniques in dental medicine has boosted the development and use of artificial intelligence (AI) systems for various clinical problems. Cone beam computed tomography (CBCT) and intraoral/facial scans are potential sources of image data to develop 3D [...] Read more.
The increasing use of three-dimensional (3D) imaging techniques in dental medicine has boosted the development and use of artificial intelligence (AI) systems for various clinical problems. Cone beam computed tomography (CBCT) and intraoral/facial scans are potential sources of image data to develop 3D image-based AI systems for automated diagnosis, treatment planning, and prediction of treatment outcome. This review focuses on current developments and performance of AI for 3D imaging in dentomaxillofacial radiology (DMFR) as well as intraoral and facial scanning. In DMFR, machine learning-based algorithms proposed in the literature focus on three main applications, including automated diagnosis of dental and maxillofacial diseases, localization of anatomical landmarks for orthodontic and orthognathic treatment planning, and general improvement of image quality. Automatic recognition of teeth and diagnosis of facial deformations using AI systems based on intraoral and facial scanning will very likely be a field of increased interest in the future. The review is aimed at providing dental practitioners and interested colleagues in healthcare with a comprehensive understanding of the current trend of AI developments in the field of 3D imaging in dental medicine. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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23 pages, 805 KiB  
Review
Digital Undergraduate Education in Dentistry: A Systematic Review
by Nicola U. Zitzmann, Lea Matthisson, Harald Ohla and Tim Joda
Int. J. Environ. Res. Public Health 2020, 17(9), 3269; https://doi.org/10.3390/ijerph17093269 - 07 May 2020
Cited by 96 | Viewed by 10095
Abstract
The aim of this systematic review was to investigate current penetration and educational quality enhancements from digitalization in the dental curriculum. Using a modified PICO strategy, the literature was searched using PubMed supplemented with a manual search to identify English-language articles published between [...] Read more.
The aim of this systematic review was to investigate current penetration and educational quality enhancements from digitalization in the dental curriculum. Using a modified PICO strategy, the literature was searched using PubMed supplemented with a manual search to identify English-language articles published between 1994 and 2020 that reported the use of digital techniques in dental education. A total of 211 articles were identified by electronic search, of which 55 articles were selected for inclusion and supplemented with 27 additional publications retrieved by manual search, resulting in 82 studies that were included in the review. Publications were categorized into five areas of digital dental education: Web-based knowledge transfer and e-learning, digital surface mapping, dental simulator motor skills (including intraoral optical scanning), digital radiography, and surveys related to the penetration and acceptance of digital education. This review demonstrates that digitalization offers great potential to revolutionize dental education to help prepare future dentists for their daily practice. More interactive and intuitive e-learning possibilities will arise to stimulate an enjoyable and meaningful educational experience with 24/7 facilities. Augmented and virtual reality technology will likely play a dominant role in the future of dental education. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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15 pages, 734 KiB  
Review
Big Data and Digitalization in Dentistry: A Systematic Review of the Ethical Issues
by Maddalena Favaretto, David Shaw, Eva De Clercq, Tim Joda and Bernice Simone Elger
Int. J. Environ. Res. Public Health 2020, 17(7), 2495; https://doi.org/10.3390/ijerph17072495 - 06 Apr 2020
Cited by 27 | Viewed by 10172
Abstract
Big Data and Internet and Communication Technologies (ICT) are being increasingly implemented in the healthcare sector. Similarly, research in the field of dental medicine is exploring the potential beneficial uses of digital data both for dental practice and in research. As digitalization is [...] Read more.
Big Data and Internet and Communication Technologies (ICT) are being increasingly implemented in the healthcare sector. Similarly, research in the field of dental medicine is exploring the potential beneficial uses of digital data both for dental practice and in research. As digitalization is raising numerous novel and unpredictable ethical challenges in the biomedical context, our purpose in this study is to map the debate on the currently discussed ethical issues in digital dentistry through a systematic review of the literature. Four databases (Web of Science, Pub Med, Scopus, and Cinahl) were systematically searched. The study results highlight how most of the issues discussed by the retrieved literature are in line with the ethical challenges that digital technologies are introducing in healthcare such as privacy, anonymity, security, and informed consent. In addition, image forgery aimed at scientific misconduct and insurance fraud was frequently reported, together with issues of online professionalism and commercial interests sought through digital means. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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Other

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5 pages, 268 KiB  
Letter
Digital Oral Medicine for the Elderly
by Christian E. Besimo, Nicola U. Zitzmann and Tim Joda
Int. J. Environ. Res. Public Health 2020, 17(7), 2171; https://doi.org/10.3390/ijerph17072171 - 25 Mar 2020
Cited by 5 | Viewed by 2543
Abstract
Sustainable oral care of the elderly requires a holistic view of aging, which must extend far beyond the narrow field of dental expertise to help reduce the effects of sociobiological changes on oral health in good time. Digital technologies now extend into all [...] Read more.
Sustainable oral care of the elderly requires a holistic view of aging, which must extend far beyond the narrow field of dental expertise to help reduce the effects of sociobiological changes on oral health in good time. Digital technologies now extend into all aspects of daily life. This review summarizes the diverse digital opportunities that may help address the complex challenges in Gerodontology. Systemic patient management is at the center of these descriptions, while the application of digital tools for purely dental treatment protocols is deliberately avoided. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
8 pages, 275 KiB  
Letter
Recent Trends and Future Direction of Dental Research in the Digital Era
by Tim Joda, Michael M. Bornstein, Ronald E. Jung, Marco Ferrari, Tuomas Waltimo and Nicola U. Zitzmann
Int. J. Environ. Res. Public Health 2020, 17(6), 1987; https://doi.org/10.3390/ijerph17061987 - 18 Mar 2020
Cited by 61 | Viewed by 8232
Abstract
The digital transformation in dental medicine, based on electronic health data information, is recognized as one of the major game-changers of the 21st century to tackle present and upcoming challenges in dental and oral healthcare. This opinion letter focuses on the estimated top [...] Read more.
The digital transformation in dental medicine, based on electronic health data information, is recognized as one of the major game-changers of the 21st century to tackle present and upcoming challenges in dental and oral healthcare. This opinion letter focuses on the estimated top five trends and innovations of this new digital era, with potential to decisively influence the direction of dental research: (1) rapid prototyping (RP), (2) augmented and virtual reality (AR/VR), (3) artificial intelligence (AI) and machine learning (ML), (4) personalized (dental) medicine, and (5) tele-healthcare. Digital dentistry requires managing expectations pragmatically and ensuring transparency for all stakeholders: patients, healthcare providers, university and research institutions, the medtech industry, insurance, public media, and state policy. It should not be claimed or implied that digital smart data technologies will replace humans providing dental expertise and the capacity for patient empathy. The dental team that controls digital applications remains the key and will continue to play the central role in treating patients. In this context, the latest trend word is created: augmented intelligence, e.g., the meaningful combination of digital applications paired with human qualities and abilities in order to achieve improved dental and oral healthcare, ensuring quality of life. Full article
(This article belongs to the Special Issue Big Data in Dental Research and Oral Healthcare)
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