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The integration of artificial intelligence (AI) into prosthodontics has significantly improved diagnostic accuracy and treatment planning precision. This research evaluates the efficacy of four prominent object detection algorithms--YOLOv7, YOLOv8, AdaBoost, and RCNN--in identifying dental implants from radiographic images. Using a custom dataset containing over 5000 images collected from dental clinics, the study conducts a thorough assessment of each algorithm's performance. The proposed approach involves data processing and model training. This comparative analysis provides valuable insights into the performance characteristics of each algorithm, particularly regarding dental implant identification. Such insights can assist prosthodontists in making informed decisions regarding algorithm selection for clinical implementation, ultimately enhancing patient care and treatment outcomes in the field of dental prosthetics. Findings suggest that YOLOv7 and YOLOv8 excel in both speed and accuracy of dental implant identification, with AdaBoost also performing admirably, although with slightly slower processing times. However, RCNN, despite its precise localization capabilities, demonstrates relatively slower processing speeds. Evaluation metrics unveil varying levels of accuracy among the models, ranging from 77% to 92%. Furthermore, these findings contribute to the ongoing advancements in AI-assisted dental care, promising improved efficiency and precision in treatment planning and execution for better patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Hookah smoking has been on raise all over the world, including India, especially among youngsters. There is growing evidence suggesting the high school children experimenting this form of tobacco. Objective: The objective of this study was to investigate the characteristics, behavior, and perceptions related to hookah smoking among the hookah smokers in Mumbai. Materials and Methods: A cross-sectional survey was conducted among 200 randomly selected young adults between the age group of 15–35 years in Mumbai who visited different dental clinics. The questionnaire was distributed as Google Forms online in the month of November and December 2019 and those who submitted completed responses were included in the study. Results: Only 114 participants returned with the completed forms in the time period of 2 months. The results showed that the majority of participants were between 20 and 24 age, comprising 58% who were having the habit of hookah smoking. Among which 24% females, 76% males had history of hookah habit. Eight percent of males started smoking hookah from very young age. Males (29.89%) shared one hookah pot with four members. Forty percent of the participants stated that they are interested to smoke again because of hookah flavor. Conclusion: Easy availability of newer forms of smoking at online markets could play a role in promoting the use of hookah among youngsters. Most products are being sold without any warnings, and there is no means to control the selling of the products to minors. Educational intervention is urgently needed to create awareness among youth about the harmful effects of hookah smoking. [ABSTRACT FROM AUTHOR]