ABSTRACT
Endodontic treatment is often necessary in the field of dentistry. As the tooth structure is lost during such treatment, the tooth may become weaker and lose some of its mechanical qualities. Endodontically treated posterior teeth require cuspal coverage because of their anatomical features. Endocrowns are regarded as a suitable choice for restoring teeth that have undergone endodontic treatment. These restorations are recommended when there is a substantial loss of tooth structure, restricted interocclusal space, or a short clinical crown. They are also contraindicated in case of severe loss of tooth structure where adhesion is not applicable. Endocrowns require a specific preparation design that is distinct from the conventional crown. They can be manufactured by two methods: heat pressing or computer-aided design/computer-aided manufacturing (CAD/CAM). Moreover, several materials have been used in fabricating endocrown restoration. Lithium disilicate glass-ceramic is the most recommended material as it possesses excellent mechanical properties and esthetic results with the ability to bond to tooth structure. In conclusion, several kinds of literature recommend using them for molars. Further research is needed to evaluate this technique for premolar and anterior teeth.
ABSTRACT
Implant dentistry has witnessed a transformative shift with the integration of artificial intelligence (AI) technologies. This article explores the role of AI in implant dentistry, emphasizing its impact on diagnostics, treatment planning, and patient outcomes. AI-driven image analysis and deep learning algorithms enhance the precision of implant placement, reducing risks and optimizing aesthetics. Moreover, AI-driven data analytics provide valuable insights into patient-specific treatment strategies, improving overall success rates. As AI continues to evolve, it promises to reshape the landscape of implant dentistry and lead in an era of personalized and efficient oral healthcare.
