AI-Based Dental Disease Diagnosis Using Multimodal Data

Abstract

Dental diseases are among the most common global health problems, often resulting from poor oral hygiene, late diagnosis, or inconsistent clinical evaluation. The human oral cavity hosts a complex and dynamic microbial ecosystem, comprising over 700 bacterial species, alongside fungi, viruses, and protozoa. Traditional diagnostic processes rely heavily on manual interpretation of dental X-rays, laboratory tests, and patient history, which increases the risk of misdiagnosis.This research proposes an AI-based multimodal diagnostic system that integrates radiographic images, laboratory test data, and patient medical history to provide more accurate and comprehensive dental disease detection. The system utilizes machine learning and deep learning models for feature extraction and fusion, enabling improved diagnostic reliability.The current study focuses on the design, methodology, and planned evaluation of the system, with the objective of assisting dentists in clinical decision-making and enhancing patient care through a unified, intelligent diagnostic tool.

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