Mouth ulcers, also known as aphthous ulcers, are common oral lesions that can cause discomfort and pain for individuals. The accurate and timely diagnosis of mouth ulcers is crucial for effective treatment and management. Artificial intelligence (AI) has emerged as a promising tool in healthcare, offering the potential to enhance diagnostic accuracy and efficiency. This paper aims to explore the application of AI in the diagnosis of mouth ulcers.The study begins by reviewing the existing literature on mouth ulcers, including their etiology, clinical manifestations, and conventional diagnostic approaches. Subsequently, it delves into the advancements in AI techniques, such as machine learning, deep learning, and natural language processing, that have facilitated the development of AI-based diagnostic models.Various datasets used in training and evaluating AI models for mouth ulcer diagnosis are examined, encompassing clinical images, patient medical histories, and relevant oral health data.