Artificial Intelligence in Endodontics: Current Applications and Future Directions.

Artificial intelligence (AI) has remarkably increased its presence and significance in a wide range of sectors, including dentistry. It can mimic the intelligence of humans to undertake complex predictions and decision-making in the healthcare sector, particularly in endodontics. The models of AI, such as convolutional neural networks and/or artificial neural networks, have shown a variety of applications in endodontics, including studying the anatomy of the root canal system, forecasting the viability of stem cells of the dental pulp, measuring working lengths, pinpointing root fractures and periapical lesions and forecasting the success of retreatment procedures. Future applications of this technology were considered in relation to scheduling, patient care, drug-drug interactions, prognostic diagnosis, and robotic endodontic surgery. In endodontics, in terms of disease detection, evaluation, and prediction, AI has demonstrated accuracy and precision. AI can aid in the advancement of endodontic diagnosis and therapy, which can enhance endodontic treatment results. However, before incorporating AI models into routine clinical operations, it is still important to further certify the cost-effectiveness, dependability, and applicability of these models.

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Artificial Intelligence in Dentistry: Past, Present, and Future

Accuracy of different generations of apex locators in determining working length; a systematic review and meta-analysis

Background. This study aimed to assess the accuracy of three electronic apex locators (EALs) (Dentaport ZX [J Morita, Tokyo, Japan], Propex Pixi [Dentsply Maillefer, Ballaigues, Switzerland], and iPex II [NSK, Tokyo, Japan]) during root canal retreatment. Methods. The root canal lengths of 90 extracted single-rooted human teeth were determined under a dental operating microscope at ×10 magnification. The actual working length (AWL) was 0.5 mm less than the root length. Electronic measurements were performed with the three EALs. The root canals were instrumented and filled to the actual working length using the lateral compaction technique. After seven days, the teeth were retreated until the retreatment file was applied to the root canal at the working length determined by EALs, and then, the three EALs were used for determining the retreatment working length. Data were analyzed using chi-squared and Kruskal-Wallis tests. Results. In the retreatment, the accuracy of EALs was reported at %83.3 for Dentaport ZX, %83.4 forPropex Pixi, and %80 for iPex II within a tolerance of 0.5± mm of the AWL. Conclusion. Under the limitations of this study, Dentaport ZX, Propex Pixi, and iPex II can be a useful adjunct during retreatment. Clinicians should be aware that residual materials in the root canal during retreatment can affect the accuracy of EALs.

https://joddd.tbzmed.ac.ir/PDF/joddd-14-125.pdf

Susana Gomes-Azevedo

Papers

In Vivo Evaluation of 3 Electronic Apex Locators: Root ZX Mini, Apex ID, and Propex Pixi