AI-Assisted Thermal Imaging for Gingival Inflammation Assessment: A Novel Approach

This study investigates a novel approach for detecting gingival inflammation using thermal imaging and artificial intelligence (AI). Thermal imaging is a technique that utilizes heat to generate detailed images, while AI assists in analyzing these images to identify patterns. Unlike traditional methods that require direct contact or visual examination, this approach is non-invasive, eliminating the need for physical interaction with the gingiva or reliance on subjective assessments.

A key aspect of this study is its focus on individuals with mouth breathing, a condition that complicates gingival health monitoring. By utilizing thermal imaging, the study successfully detected and classified gingival inflammation levels (healthy, mild, moderate, or severe) based on heat distribution patterns. Additionally, specific temperature thresholds were established to differentiate between healthy and inflamed gingival tissues in this patient group, representing a novel contribution to the field.

The developed AI system demonstrated high accuracy in identifying inflammation. This technology has the potential to facilitate earlier detection of gingival disease, even before clinical symptoms become evident. Furthermore, it offers a fast, painless, and reliable method for monitoring gingival health over time, enhancing accessibility and improving patient experience in dental care.

These findings suggest that the integration of thermal imaging and AI could significantly improve the diagnosis and management of gingival diseases. Future research could further refine this technology by expanding the sample size and optimizing analytical models to enhance accuracy and widespread applicability.