A Digital Framework for Early Oral Disease Detection and Patient–Provider Integration in Preventive Dentistry

Filieieva Viktoriia

Citation: Filieieva Viktoriia, "A Digital Framework for Early Oral Disease Detection and Patient–Provider Integration in Preventive Dentistry", Universal Library of Medical and Health Sciences, Volume 03, Issue 04.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The accelerating integration of artificial intelligence (AI) and teledentistry into oral healthcare creates an urgent need for systematic digital frameworks capable of unifying early disease detection with seamless patient–provider communication. This study aims to analyse existing evidence on AI-assisted diagnostic tools, teledentistry platforms, and patient engagement mechanisms in order to synthesise a structured five-layer digital framework for preventive dentistry. A systematic literature review and comparative case analysis were conducted using 20 peer-reviewed sources. Results indicate that deep learning algorithms reach diagnostic accuracy exceeding 90% for caries and periodontal disease, while multimodal architectures achieve AUC values above 0.92 for oral cancer risk stratification. Integrated teledentistry workflows reduce first-consultation delays by up to 73% and improve patient adherence to preventive protocols. The proposed framework consolidates data input, AI processing, decision support, patient–provider integration, and outcome monitoring into a coherent operational model. Findings are relevant to dental practitioners, health informaticists, healthcare administrators, and policymakers seeking evidence-based strategies for digital transformation in preventive oral care.


Keywords: Preventive Dentistry, Artificial Intelligence, Deep Learning, Early Oral Disease Detection, Teledentistry, Patient–Provider Integration, Digital Health Framework, Convolutional Neural Networks, Electronic Health Records, Oral Cancer Screening.

Download doi https://doi.org/10.70315/uloap.ulmhs.2025.0304011