Introduction
Artificial intelligence (AI), which encompasses subfields such as machine learning and deep learning, is a branch of computer science and engineering devoted to developing machines that can perform tasks requiring human-like intelligence. These tasks include visual perception, decision-making, and natural language processing. AI applications are becoming increasingly common in oral healthcare, leading to heightened expectations as well as ethical and practical concerns.
Objectives
This critical review assessed current applications of AI in oral healthcare and identified key perspectives, challenges, and limitations in ongoing AI research.
Results
AI models have been applied across various specialties in oral health, aiding in diagnosis, treatment planning, and decision-making. They also help reduce the burden of repetitive tasks and optimize clinical workflows. However, ethical complexities and methodological limitations, such as inconsistent data quality, risks of bias, lack of transparency, and insufficient clinical validation, diminish the quality of AI studies and impede the effective integration of AI into routine oral healthcare.
Conclusions
A diverse range of diagnostic and prognostic AI-based models has been developed across nearly all specialties in oral medicine. These models utilize machine learning algorithms and have the potential to transform how oral health professionals conduct treatment planning, including enhancing the provision of unbiased, accurate, and personalized oral healthcare.
To advance AI research, studies must adhere to standardized methodological and ethical guidelines, particularly regarding data collection. Ensuring transparency, privacy, and accountability is essential. Developing a comprehensive framework to produce robust, reproducible AI research, along with clinically validated technologies, will facilitate the smooth integration of AI into clinical practice. This shift will benefit both clinicians and patients by improving oral healthcare outcomes.
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