cover
Contact Name
Rizky Merdietio Boedi
Contact Email
rizkymerdietio@lecturer.undip.ac.id
Phone
+6281222707744
Journal Mail Official
actaodontologica@fk.undip.ac.id
Editorial Address
Department of Dentistry, Faculty of Medicine, Universitas Diponegoro. Jl. Prof. Moeljono S Trastotenojo, Building D, Floor 5, Tembalang, Semarang, Central Java, Indonesia. 50275.
Location
Kota semarang,
Jawa tengah
INDONESIA
Acta Odontologica Indonesia
Published by Universitas Diponegoro
ISSN : -     EISSN : 30907411     DOI : https://doi.org/10.14710/actodont
Core Subject : Health,
Acta Odontologica Indonesia is a single-blind peer-reviewed journal in the field of dentistry. We publish high-quality research and review articles spanning clinical, theoretical, and applied studies across a broad discipline of dental science and practice. We welcome original research articles and comprehensive reviews that explore cutting-edge advancements, evidence-based practices, and emerging trends across a wide range of topics of dentistry. Acta Odontologica Indonesia seeks to promote the integration of diverse perspectives and disciplines to advance scientific knowledge and improve clinical outcomes in dentistry.
Articles 22 Documents
Diagnostic Accuracy of Mobile Dental AI Applications for Early Oral Disease Detection: A Systematic Review Maqbool Noori; Erni Marlina; Andi Sri Permatasari; Fadhlil Ulum A. Rahman
Acta Odontologica Indonesia 2026: December Edition (Article in Press)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/actodont.31922

Abstract

Early detection of oral diseases, particularly dental caries, is critical for effective prevention and timely intervention. However, conventional diagnostic approaches are limited by subjectivity, inter-clinician variability, and unequal access to dental services. Recently, mobile-based artificial intelligence (AI) applications have emerged as potential tools to support early oral disease screening, especially in underserved and resource-limited settings. Despite increasing interest, evidence regarding their diagnostic accuracy and reliability remains fragmented.This systematic review aimed to evaluate the diagnostic accuracy and reliability of mobile-based artificial intelligence applications for early detection of oral diseases, with a primary focus on dental caries.A systematic review was conducted in accordance with PRISMA DTA guidelines. Electronic databases, including PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar, were searched for peer-reviewed studies published between 2015 and 2025. Eligible studies evaluated smartphone-based or mobile AI applications for dental caries detection and reported diagnostic performance metrics. Study selection, data extraction, and methodological quality assessment were performed using predefined criteria, with study quality assessed using the QUADAS-2 tool. Due to heterogeneity across studies, findings were synthesized narratively.Eighteen studies met the inclusion criteria. Mobile dental AI applications demonstrated moderate to high diagnostic accuracy, with reported sensitivity ranging from approximately 75% to over 95% and specificity from approximately 70% to 96%. AI-assisted systems showed performance comparable to professional dental assessment under controlled conditions, although most studies relied on internal validation.In conclusion, mobile based AI applications show promising diagnostic accuracy for early detection of dental caries and may serve as adjunctive screening tools in preventive oral healthcare. However, further large-scale studies with robust external validation are required before widespread clinical implementation.
Consistency between Undergraduate and Graduate Students using Two Dental Staging Systems — A Pilot Study Roberta Pinto; Maria Eduarda Causs; Débora Moreira; Nikolaos Angelakopoulos; Ademir Franco
Acta Odontologica Indonesia 2026: December Edition (Article in Press)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/actodont.33953

Abstract

Radiographic dental staging remains one of the most frequently applied approaches for subadult dental age assessment in forensic odontology. In this preliminary study, we compared the consistency across observers with different academic level applying two staging systems. Methods: Forty-six participants composed four groups according to academic level: undergraduate (n = 16), specialization (n = 13), master’s (n = 10), and doctoral students (n = 7). Each participant assessed 10 panoramic radiographs from individuals aged 6.5–13.5 years (mean: 9.45 ± 2.45 years), staging seven left permanent mandibular teeth (International Dental Federation: 31–37) using both Demirjian’s and Moorrees’ systems. A total of 920 radiographic assessments and 6,440 dental stage allocations were generated. Observer consistency was assessed separately for each tooth, staging system, and academic level-based group using weighted Fleiss’ kappa coefficients with ordinal weights and 95% confidence intervals. Results: Staging performance using Demirjian’s and Moorrees’ systems by observers with different academic levels showed similar consistency. Absolute differences between systems remained below 0.10 in 92.9% of the comparisons. Teeth 31 and 36 generally presented the lowest consistency estimates across staging systems and observer groups, whereas tooth 34 frequently showed among the highest consistency values. Despite the discrete differences, the largest absolute differences between Demirjian's and Moorrees' systems varied according to the observers' educational background, being more evident for teeth 31, 36, and 37, while the remaining teeth showed even more discrete differences between staging systems. Conclusion: Despite the discrete differences observed between staging through Demirjian’s and Moorrees’ systems, the results of this study should be carefully interpreted since it presented a preliminary point-specific assessment of consistency and not accuracy. Future studies should implement comparisons with gold standard observers and with chronological age to enable accuracy estimates.

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