Digital dentistry has witnessed significant advancements in recent years, driven by extensive research following the
introduction of cutting-edge technologies such as CAD/CAM and 3D oral scanners. Until now, 2D images obtained via
x-ray or CT scans we...
Digital dentistry has witnessed significant advancements in recent years, driven by extensive research following the
introduction of cutting-edge technologies such as CAD/CAM and 3D oral scanners. Until now, 2D images obtained via
x-ray or CT scans were critical to detect anomalies and for decision-making. This review describes the main principles
and applications of supervised, unsupervised, and reinforcement learning in medical applications. In this context,
we present a diverse range of artificial intelligence networks with potential applications in dentistry, accompanied by
existing results in the field.