Emerging Trends in The Study of Natal Teeth: A Review of Clinical Findings and Predictive Modelling Using Machine Learning
DOI:
https://doi.org/10.63682/jns.v14i26S.6575Keywords:
Natal, Teeth, Machine LearningAbstract
Natal teeth, present at birth, are rare developmental anomalies that pose both clinical and diagnostic challenges. These teeth are often associated with complications such as feeding difficulties, oral trauma, and in some cases, systemic syndromes. Traditional understanding of natal teeth is based primarily on case reports and small-scale clinical studies, which offer limited insight into broader patterns and predictive factors. With the advent of machine learning (ML) in healthcare, there is growing interest in using computational approaches to identify predictive indicators and enhance early diagnosis. This review synthesizes recent clinical literature on natal teeth and explores the potential application of ML techniques for predictive modeling. The integration of clinical findings with AI-based tools could pave the way for improved diagnostics and proactive neonatal care
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Massler M, Savara BS. “Natal and neonatal teeth: A review of 24 cases reported in the literature”. J Pediatr. 1950;36:349-59.
Ardeshana A, Bargale S, Karri A, Dave B. “Dentitia praecox - natal teeth: a case report and review”. Journal of Applied Dental and Medical Sciences. 2016;2(1).
Mhaske S, Yuwanati MB, Mhaske A, Raghavendra R, Kamath K, Saawarn S. “Natal and neonatal teeth-an overview of the literature”, Hindawani publishing corporation ISRN Paediatrics. 2013;2013:956269.
Boyd, JD, Miles, AE. “Erupted teeth in Ciclops faetus.” Br Dent J. 1951;91:173.
P. Mishra and R. Jain, “Natal and Neonatal Teeth: A Review of Clinical Features and Management,” Pediatric Dentistry, vol. 45, no. 1, pp. 14–21, Jan. 2023.
S. Deshmukh et al., “Natal tooth in a 2-month-old infant: A case report,” Int. J. Contemp. Pediatr., vol. 11, no. 1, pp. 187–189, Jan. 2024.
Bigeard L, Hemmerle J, Sommermater JI. “Clinical and ultrastructural study of the natal tooth: enamel and dentin assessments.” J Dent Child. 1996;63:23-31.
M. Sharma and A. Kaur, “Management of natal teeth in neonates: A case study,” Int. J. Contemp. Pediatr., vol. 11, no. 2, pp. 302–304, Feb. 2024.
Jasmin JR, Clergeau-Guerithalt. “A scanning electron microscopic study of the enamel of neonatal teeth.” J Biol Buccale. 1991;19:309-14.
Anderson RA. “Natal and neonatal teeth: histologic investigation of two black females”. J Dent Child. 1982;49:300-03.
Rao RS, Mathad SV. “Natal teeth: Case report and review of literature.” J Oral Maxillofac Pathol. 2009;13(1):41–46
Buchanan S, Jenkins CR. Riga-Fedes syndrome: natal or neonatal teeth associated with tongue ulceration: Case report. Aust Dent J. 1997;42:225–27.
Tomizawa M, Yamada Y, Tonouchi K, Watanabe H, Noda T. “Treatment of RigaFede’s disease by resin-coverage of the incisal edges and seven cases of natal and neonatal teeth”. Shoni Shikagaku Zasshi. 1989;27:182–90.
Hedge RJ. “Sublingual traumatic ulceration due to neonatal teeth (Riga-Fede disease)” J Indian Soc Pedod Prev Dent. 2005;3:51–52.
Vidya Albert Yen, Niraimathy Kuppuswami, “Incidence of Natal Teeth in Newborns in Government Medical College and Hospital, Chengalpattu: A Pilot Study”, Journal of Clinical and Diagnostic Research. 2017 Apr, Vol-11(4): ZC86-ZC88
Gokul Gunasekaran, Geo Mani, Sri Rengalakshmi, ‘Prevalence of Natal or Neonatal Teeth in Paediatric Dental Patients in Chennai – A retrospective study”, Palarch’s Jounal of Archaelogy of Egypt/Egyptology 17(7), 217-226, ISSN 1567-214x
A. Singh and V. Joshi, “Machine Learning Applications in Pediatric Dental Anomalies: A Systematic Review,” Appl. Sci., vol. 13, no. 2, p. 788, Jan. 2023
J. Lin et al., “Deep Learning for Tooth Development Staging Using YOLOv5,” BMC Oral Health, vol. 24, no. 1, p. 160, Mar. 2024.
K. Mehta and R. Soni, “Explainable Artificial Intelligence in Dental Forensics: SHAP-Based Model Interpretation,” arXiv preprint, arXiv:2308.05967, Aug. 2023.
S. Gupta, “Ethical Implications and Challenges in AI-Powered Pediatric Dentistry,” Biomedicines, vol. 11, no. 3, p. 788, Mar. 2023.
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