Charting Ethical Terrain: The Functon of Artificial Intelligence in Oral and Maxillofacial Imaging

Abstract

The integration of artificial intelligence (AI) into maxillofacial imaging represents a significant advancement in diagnostics and therapy. This review explores the ethical implications of AI in this specialized area, addressing concerns such as data privacy, informed consent, and algorithmic bias. It highlights the potential benefits of AI for patient outcomes and clinical efficiency while acknowledging risks associated with reliance on automated systems. The review aims to establish a framework for ethical guidelines to ensure that AI enhances patient care. AI's application in various industries has gained momentum, with dentistry, particularly oral and maxillofacial radiology, emerging as a promising field. Recent studies have focused on convolutional neural networks for tasks such as image classification, detection, segmentation, and refinement. These AI systems support radiographic diagnosis, image analysis, forensic dentistry, and image quality enhancement. However, optimal performance requires large, well-labeled datasets, necessitating significant input from oral and maxillofacial radiologists, which can be time-intensive. For AI to be effectively integrated into clinical practice, several challenges must be overcome, including the creation of comprehensive open datasets, understanding AI judgment criteria, and addressing DICOM hacking threats. By developing solutions alongside AI advancements, the technology can significantly evolve, potentially transforming automated diagnosis, treatment planning, and tool development. Oral and maxillofacial radiologists will play a crucial role in shaping AI applications in their field, leveraging their expertise in interpreting radiographic images.

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