Automated Identification of Dental Implants: A New, Fast and Accurate Artificial Intelligence System.

INTRODUCTION: Prosthetic complications that occur to some implant prosthetics may require removal of the prosthesis for replacement or repair. Therefore, the presence of a technique to identify the type of dental implant is mandatory to provide the suitable components. Hence, the aim of the current study was to evaluate the accuracy of YOLOv8 object detection algorithm in automatic identification of the type of dental implant from digital periapical radiographs. METHODS: YOLOv8m-seg object detection algorithm was used to build a model to automatically identify the type of dental implant. A set of 2573 digital periapical radiographs for six distinct dental implants manufacturers were used to train the model. The outcomes were evaluated using precision, recall, F1 score and mAP. RESULTS: The overall accuracy of the YOLOv8m-seg model in terms of precision, recall, F1 score and mAP revealed values of 0.919, 0.98, 0.95 and 0.972 respectively. The average detection speed of the images was 1.3 seconds. The model was able to detect and identify multiple implants simultaneously on the same image. CONCLUSIONS: YOLOv8m-seg object detection algorithm is promising in identification of dental implants from periapical radiographs with high detection accuracy (97.2%), fast detection results and multi-implant detection from the same image. CLINICAL SIGNIFICANCE: This AI system can accurately identify the type of osseointegrated dental implants enabling dentists to provide the appropriate prosthetic components even if different implant systems are used within the same patient. This can save tremendous amounts of time, effort and cost for both the dentist and the patient.

Arabic sign language: a perspective.

Sign language in the Arab World has been recently recognized and documented. Many efforts have been made to establish the sign language used in individual countries, including Jordan, Egypt, Libya, and the Gulf States, by trying to standardize the language and spread it among members of the Deaf community and those concerned. Such efforts produced many sign languages, almost as many as Arabic-speaking countries, yet with the same sign alphabets. This article gives a tentative account of some sign languages in Arabic through reference to their possible evolution, which is believed to be affected by the diglossic situation in Arabic, and by comparing some aspects of certain sign languages (Jordanian, Palestinian, Egyptian, Kuwaiti, and Libyan) for which issues such as primes, configuration, and movement in addition to other linguistic features are discussed. A contrastive account that depicts the principal differences among Arabic sign languages in general and the spoken language is given.