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Healthcare
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Dental Research and Innovation: Shaping the Future of Oral Health
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Dental Research and Innovation: Shaping the Future of Oral Health

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: 31 May 2027 | Viewed by 4090

Special Issue Editors

Prof. Dr. Mihai Rominu

E-Mail Website
Guest Editor
Department of Prostheses Technology and Dental Materials, “Victor Babes” University of Medicine and Pharmacy, 300070 Timisoara, Romania
Interests: prostheses technology; composite resins; adhesives; interfaces
Special Issues, Collections and Topics in MDPI journals
Dr. Ioana Veja

E-Mail Website
Guest Editor Assistant
Department of Dental Medicine, Faculty of Dentistry, “Vasile Goldiș” Western University of Arad, 310025 Arad, Romania
Interests: periodontal regeneration; biomaterials; dental materials; tooth-periodontal interactions; dental adhesion

Special Issue Information

Dear Colleagues,

This Special Issue, “Dental Research and Innovation: Shaping the Future of Oral Health”, aims to spotlight recent innovations and clinically relevant advances that enhance patient outcomes in dental medicine. As the field continues to evolve with digital technologies, evidence-based protocols, and interdisciplinary collaboration, this Issue focuses on topics that directly impact patient care, oral health, and clinical decision-making.

We welcome original research articles, reviews, and case series that examine clinically applied advancements in dental diagnostics, therapeutic procedures, and patient-centered strategies. Submissions should emphasize outcomes that contribute to improved diagnosis, treatment, prevention, or professional competencies in dental practice.

Topics of interest include, but are not limited to

  • Clinical applications of digital dentistry and artificial intelligence to improve diagnosis and treatment planning;
  • Evidence-based advances in restorative and minimally invasive dentistry focused on preserving oral function and health;
  • Periodontics, endodontics, and implantology with a focus on therapeutic innovation and long-term outcomes;
  • Orthodontics and craniofacial research addressing clinical challenges and solutions;
  • Oral–systemic health interactions and public health strategies that impact clinical dental care;
  • Innovations in professional dental education and digital training that enhance care quality and practitioner expertise.

We look forward to receiving your valuable contributions that bridge research and clinical practice for better patient care.

Prof. Dr. Mihai Rominu
Guest Editor

Dr. Ioana Veja
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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. Healthcare is an international peer-reviewed open access semimonthly 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 2700 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

  • digital dentistry
  • artificial intelligence in dentistry
  • biomaterials
  • orthodontics
  • endodontics
  • periodontics
  • oral–systemic health
  • dental public health
  • esthetic dentistry
  • implantology
  • prosthodontics

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
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  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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18 pages, 615 KB  
Article
Assessment of Oral Hygiene Practices, Adjunctive Cleaning Methods, and Their Impact on Plaque and Gingival Indices Among Young Adults in Urban and Rural Settings in Romania
by Ioana Elena Lile, Șerban Talpoș-Niculescu, Diana Marian, Otilia Stana, Andra-Alexandra Stăncioiu, Alexandru Cătălin Motofelea and George-Dumitru Constantin
Healthcare 2025, 13(22), 2970; https://doi.org/10.3390/healthcare13222970 - 19 Nov 2025
Cited by 4 | Viewed by 1244
Abstract
Background/Objectives: Young adults increasingly prefer natural dentifrices; however, the short-term clinical effects and behavioural correlates of these products remain insufficiently documented. This study aimed to evaluate the associations between daily oral-hygiene practices, adjunctive cleaning methods, and plaque and gingival indices, and to compare [...] Read more.
Background/Objectives: Young adults increasingly prefer natural dentifrices; however, the short-term clinical effects and behavioural correlates of these products remain insufficiently documented. This study aimed to evaluate the associations between daily oral-hygiene practices, adjunctive cleaning methods, and plaque and gingival indices, and to compare the short-term effects of three natural toothpaste formulations—sodium bicarbonate, activated charcoal, and lemon-based. Methods: In this cross-sectional study, 101 Romanian adults (aged 20–41 years; 69.3% urban) completed a structured questionnaire assessing brushing frequency and the use of dental floss, interdental stimulators, and mouth rinses. Clinical assessments included the Silness–Löe Plaque Index and the Löe–Silness Gingival Index (modified by Lobene), recorded immediately before and after a supervised 2 min brushing session using the Bass technique with soft-bristled brushes and the participant’s self-reported natural toothpaste (baking soda: n = 42; charcoal: n = 27; lemon: n = 32). Results: Before brushing, 78.2% of participants presented with thin adherent plaque, while the gingival status was normal in 72.3%, mildly inflamed in 22.8%, and moderately inflamed in 5.0%. After brushing, the proportion with normal gingiva increased to 77.2%, and the proportion of thin, adherent plaque decreased to 22.8%. Brushing frequency was positively correlated with plaque reduction (ρ = 0.42, p < 0.001), while the use of adjunctive cleaning methods was inversely correlated with post-brushing gingival inflammation (ρ = −0.36, p = 0.002). Gingival improvement differed significantly among toothpaste types (χ2, p < 0.001), with formulations containing baking soda and lemon showing slightly more favourable short-term gingival categories than charcoal; these patterns are descriptive and do not demonstrate comparative product efficacy. Urban–rural differences were observed for brushing frequency (p < 0.001) and periodontal status with fewer lesions among urban participants (p = 0.002). Conclusions: A single supervised Bass-technique brushing session resulted in measurable short-term improvements in plaque and gingival indices among young adults. Sodium bicarbonate and lemon-based dentifrices appeared to be associated with slightly more favourable short-term gingival responses than charcoal, although these findings should be interpreted as preliminary. These findings emphasise the importance of consistent brushing and interdental cleaning behaviours and highlight the need for longitudinal randomised trials to evaluate the durability, safety, and comparative effectiveness of natural versus conventional dentifrices. Given the cross-sectional, single-session design, these findings are exploratory and do not establish causal or comparative product efficacy. Full article
(This article belongs to the Special Issue Dental Research and Innovation: Shaping the Future of Oral Health)
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13 pages, 867 KB  
Article
Association Between Common Systemic Medications and the Presence and Severity of Furcation Involvement: A Cross-Sectional Study
by Georgios S. Chatzopoulos and Larry F. Wolff
Healthcare 2025, 13(22), 2930; https://doi.org/10.3390/healthcare13222930 - 16 Nov 2025
Viewed by 759
Abstract
Background/Objectives: While furcation involvement is a known predictor for tooth loss, the role of systemic medications is understudied. This study aimed to investigate the association between common systemic medications and both the presence and severity of furcation involvement in a large patient cohort. [...] Read more.
Background/Objectives: While furcation involvement is a known predictor for tooth loss, the role of systemic medications is understudied. This study aimed to investigate the association between common systemic medications and both the presence and severity of furcation involvement in a large patient cohort. Methods: This retrospective cross-sectional study analyzed electronic health records from 15,881 patients within the BigMouth Dental Data Repository. The association between demographics, medication use (ACE inhibitors, statins, anti-coagulants, antidepressants, bisphosphonates, proton pump inhibitors), and the presence of furcation involvement was assessed using Chi-Square tests and multivariate logistic regression. The statistically significant relationship between medications and furcation severity (Grades 1–4) was analyzed using multinomial logistic regression. Results: Being male (OR: 1.34) and of non-Hispanic ethnicity (OR: 1.36) were significant demographic predictors for furcation involvement. After adjusting for demographics, use of ACE inhibitors (OR: 1.40), anti-coagulants (OR: 1.19), and statins (OR: 1.14) were significantly associated with higher odds of furcation involvement. Specifically, Lisinopril (OR: 1.48), Enalapril (OR: 1.83), and Atorvastatin (OR: 1.27) were significant predictors. Furthermore, patients taking Lisinopril, Aspirin, Atorvastatin, or Simvastatin had approximately 1.5 times the odds of having Grade 3 involvement compared to Grade 1 (p ≤ 0.001). Conclusions: The use of certain systemic medications, particularly for cardiovascular conditions, is independently associated with both a higher likelihood and increased severity of furcation involvement, highlighting the critical need for dental professionals to consider a patient’s medication profile as an integral part of periodontal risk assessment. Full article
(This article belongs to the Special Issue Dental Research and Innovation: Shaping the Future of Oral Health)
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Review

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8 pages, 455 KB  
Review
A Contemporary Mini-Review of Interprofessional Education and Technology-Assisted Management of Dental Emergencies in the Emergency Department
by Zanab Malik and Tony Skapetis
Healthcare 2026, 14(4), 544; https://doi.org/10.3390/healthcare14040544 - 22 Feb 2026
Viewed by 456
Abstract
Background: Dental emergencies are increasing in frequency. Numerous studies have reported minimal knowledge and/or skills by emergency department staff regarding dental emergencies. The COVID-19 pandemic has prompted a paradigm shift in emergency dental care management away from traditional management approaches. However, there have [...] Read more.
Background: Dental emergencies are increasing in frequency. Numerous studies have reported minimal knowledge and/or skills by emergency department staff regarding dental emergencies. The COVID-19 pandemic has prompted a paradigm shift in emergency dental care management away from traditional management approaches. However, there have been no reviews of contemporary literature pertaining to either technology-assisted or interprofessional education and dental emergency management in the emergency department setting. This mini-review aimed to synthesise current evidence of interprofessional education, utilising technology-assisted modalities, for the management of dental emergencies in hospital emergency departments. Methods: A comprehensive search was carried out across four electronic databases, Medline, Embase, CINAHL, and Google Scholar from 2018 to 2025. Results: A total of three papers were identified and included in the mini-review. Two of the three papers addressed the subject of dental emergencies in the emergency department as a primary finding. Discussion: Included papers were of low-quality evidence and referenced simulation-based education, tele-dentistry, and artificial intelligence as contemporary approaches relating to dental emergency management. Conclusions: This mini-review revealed minimal advances in contemporary approaches relating to both the use of technology-assisted modalities and interprofessional education for the management of dental emergencies within the hospital emergency department setting. This review provides a timely literature update for both the medical and dental professions and identifies a large gap in research surrounding this topic. Full article
(This article belongs to the Special Issue Dental Research and Innovation: Shaping the Future of Oral Health)
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Other

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17 pages, 1040 KB  
Systematic Review
Artificial Intelligence vs. Human Experts in Temporomandibular Joint MRI Interpretation: A Systematic Review
by Marijus Leketas, Inesa Stonkutė, Miglė Miškinytė and Dominykas Afanasjevas
Healthcare 2026, 14(8), 1066; https://doi.org/10.3390/healthcare14081066 - 17 Apr 2026
Viewed by 445
Abstract
Background: Magnetic resonance imaging (MRI) is the reference standard for evaluating temporomandibular joint (TMJ) disorders, particularly for assessing disc position, joint effusion, and degenerative changes. With increasing imaging demands and advances in deep learning, artificial intelligence (AI) has emerged as a potential [...] Read more.
Background: Magnetic resonance imaging (MRI) is the reference standard for evaluating temporomandibular joint (TMJ) disorders, particularly for assessing disc position, joint effusion, and degenerative changes. With increasing imaging demands and advances in deep learning, artificial intelligence (AI) has emerged as a potential adjunct to expert interpretation. This systematic review aimed to compare the diagnostic performance of AI-based models with that of human experts in TMJ MRI analysis. Methods: This review was conducted in accordance with the PRISMA 2020 guidelines and prospectively registered in PROSPERO (CRD420251174127). A systematic search of PubMed/MEDLINE, ScienceDirect, Wiley Online Library, and Springer Nature Link was performed for studies published between 2020 and 2026. Eligible studies included human participants undergoing TMJ MRI and evaluated AI, machine learning, or deep learning models against human expert interpretation. Extracted outcomes included sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and agreement metrics. Risk of bias was assessed using QUADAS-2. Due to substantial heterogeneity, a narrative synthesis was conducted. Results: Five retrospective diagnostic accuracy studies were included, comprising sample sizes ranging from 118 to 1474 patients. Target conditions included anterior disc displacement, joint effusion, osteoarthritis, and disc perforation. AI models demonstrated strong discriminative performance, with reported AUC values ranging from 0.79 to 0.98. In direct comparisons, AI achieved diagnostic accuracy comparable to experienced radiologists. AI systems frequently demonstrated higher specificity and similar overall accuracy, whereas human experts often showed higher sensitivity. In osteoarthritis assessment, AI performance approached expert level and exceeded that of less experienced readers. All studies were retrospective and predominantly single-center, with heterogeneous reference standards and limited external validation. Conclusions: AI achieves diagnostic performance comparable to experienced clinicians in TMJ MRI interpretation and shows promise as a decision-support tool. Nevertheless, it should be regarded as complementary to, rather than a replacement for, expert radiological assessment pending further rigorous validation. Full article
(This article belongs to the Special Issue Dental Research and Innovation: Shaping the Future of Oral Health)
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