Review of Classification and Early of Oral and Mouth Diseases by Using Advanced Deep Learning Methods

Abstract: Oral and mouth diseases are among the most prevalent health issues, significantly affecting individuals' quality of life and posing serious health risks if left undiagnosed. Early detection and accurate diagnosis are criticalinpreventingthe progressionofconditions suchasoral cancer and other potentially malignant disorders. Recent advancements in digital tools and deep learning have opened new avenues for improving diagnostic accuracy and accessibility. This paper tackles these issues by utilizing the InceptionResNetV2 architectureto create a robust andefficient classification system for oral diseases. The system leverages a comprehensive dataset of oral condition images, processed and trained on platforms like Google Colab or Jupyter Notebook to ensure scalability and computational efficiency. The trained model is seamlessly integrated into a Flask-based web application, allowing users touploadimages and receiveprecisediagnosticresults.Bycombiningadvanced deep learning techniques with user-friendly technology, this paper aims to facilitate early detection and diagnosis of oral diseases, enabling timely medical intervention and improving overall oral healthcare outcomes [1].