Authors:
Bharath Kumar Nagaraj

Addresses:
1Department of Artificial Intelligence, Digipulse Technologies Inc., Salt Lake City, Utah, United States of America. bharathkumarnlp@gmail.com1

Abstract:

AI diagnoses mouth ulcers in this study to increase oral healthcare diagnostic accuracy and efficiency. This study created and validated an AI model using a huge dataset of medical pictures of mouth ulcers. The collection includes a medical imaging archive, a clinical database, and research library photos. Many AI techniques are researched to develop the AI model, focusing on CNNs, RNNs, and their derivatives. The collection teaches these computers the nuanced patterns and properties of mouth ulcers. In training, gradient descent and backpropagation optimise model parameters. The oral ulcer detection and classification AI model is carefully evaluated after training. The dataset is divided into training, validation, and test sets to test model generalisation and robustness. The model's diagnostic efficacy is assessed by calculating sensitivity, specificity, accuracy, and AUC-ROC. This study indicates the AI model can diagnose oral ulcers across categories with high sensitivity and specificity. The model can quickly identify oral ulcers' presence, location, and attributes for clinical intervention and treatment planning. The AI-based technology speeds up medical image processing, standardises diagnostic criteria, and may minimise diagnostic errors. This revelation greatly affects oral healthcare clinical practice. AI-based diagnostics give doctors reliable, objective, and fast decision-making information, changing diagnoses. AI-enabled oral ulcer diagnosis improves patient outcomes, lowers healthcare costs, and speeds treatment. The AI model must be refined and validated in clinical settings despite promising outcomes. Continuous data gathering, model development, and clinical validation are needed to integrate AI-based diagnostic solutions into clinical workflows. Data privacy, AI model interpretability, and regulatory constraints must be addressed in healthcare AI research to enable ethical application.

Keywords: Artificial Intelligence; Mouth Ulcer Diagnosis; Challenges and Future Directions; Diagnosis and Treatment Initiation; Mucous Membranes of Oral Cavity; AI Technologies into Clinical Practice; Clinical Settings.

Received on: 09/03/2023, Revised on: 11/06/2023, Accepted on: 21/08/2023, Published on: 21/12/2023

FMDB Transactions on Sustainable Computer Letters, 2023 Vol. 1 No. 3, Pages: 202-209

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