International Journal of Chemical and Biochemical Sciences (ISSN 2226-9614)[/vc_column_text][/vc_column][/vc_row]
VOLUME 27(21) (2025)
Artificial Intelligence as a Diagnostic Decision Support System for Oral Lesions: An Observational Study
Salma M. Mohamed Mohy El-Din a*, Ahmed Kaboudan b, Sameh Talaat c, Hagar M. Zayed d, Suzan Seif Allah Ibrahim e
a* Demonstrator at the Department of Oral Medicine, Oral Diagnosis and Periodontology, Faculty of Dentistry, Ain Shams University, Egypt
b Professor at the Department of Oral Medicine, Oral Diagnosis and Periodontology, Faculty of Dentistry, Ain Shams University, Egypt
c Lecturer of Orthodontics, Faculty of Dentistry, Future University. Research Associate, Department of Oral Technology, University of Bonn, Germany
d Lecturer at the Department of Oral Medicine, Oral Diagnosis and Periodontolog, Faculty of Dentistry, Ain Shams University, Egypt
e Head and Professor of Oral Medicine, Periodontology and Oral Diagnosis, Faculty of Dentistry, Ain sham University, Egypt
Dean of Faculty of Oral and Dental Medicine, Nahda University, Egypt
Abstract
Early detection of oral lesions is a crucial factor in improving treatment outcomes and ensuring a better prognosis for patients. Identifying these conditions at an initial stage can reduce the risk of progression into advanced or malignant forms that significantly affect quality of life and survival. However, one of the main challenges lies in the limited knowledge and clinical experience of some general practitioners when diagnosing oral lesions. Inaccurate interpretation, false diagnosis, or inappropriate treatment can delay proper management, allowing the lesion to advance into a cancerous stage, which requires more complex interventions and has poorer outcomes. With the growing integration of technology in healthcare, artificial intelligence (AI) has emerged as a powerful tool in both medicine and dentistry. AI has been successfully applied in several diagnostic fields, demonstrating its ability to improve accuracy, efficiency, and cost-effectiveness. Building on these achievements, this study aims to develop a simple and accessible AI-based diagnostic tool that assists general practitioners in the preliminary recognition of oral mucosal lesions. The proposed tool functions using only a clinical photograph, making it highly practical in everyday practice, particularly in settings where advanced diagnostic equipment is unavailable. The implementation of such AI-assisted systems can help reduce diagnostic errors, support clinical decision-making, and promote earlier interventions. By bridging the gap between specialist expertise and general practice, this approach has the potential to improve diagnostic confidence, enhance patient care, and contribute to better oral health outcomes on a broader scale.
Keywords: Dentistry, Diagnosis, Artificial intelligence, oral mucosal lesions.
Full length article *Corresponding Author, e-mail: drsalmamohy@gmail.com, Doi # https://doi.org/10.62877/29-IJCBS-25-27-21-29