Cuba
Artificial intelligence has become increasingly integrated into dental practice, particularly through the use of imaging data such as panoramic radiographs and three-dimensional scans. This study examines the ethical, legal, and clinical implications associated with the use of dental patient data for artificial intelligence training. A central issue identified is the distinction between primary clinical use and secondary algorithmic use of patient data, which is not always explicitly addressed in current consent processes. The analysis highlights that traditional consent frameworks are often insufficient to account for large-scale data reuse, raising concerns regarding patient autonomy, transparency, and trust. In addition, the potential for reidentification of dental imaging data challenges assumptions related to anonymization and data security. Regulatory frameworks such as HIPAA, GDPR, and the EU AI Act provide partial guidance, but inconsistencies remain in their application to artificial intelligence workflows. From a clinical perspective, the use of non-representative datasets may introduce bias and affect diagnostic reliability across populations. The study emphasizes the need for improved data governance mechanisms, including dynamic consent models and privacy-preserving techniques. Overall, the findings indicate that the sustainable integration of artificial intelligence in dentistry depends on aligning technological development with ethical standards, legal compliance, and patient-centered care.
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