The role of artificial intelligence (AI) is currently increasing in terms of diagnosing diseases and planning treatment in endodontics. However, findings from individual research studies are not systematically reviewed and compiled together. Hence, this study aimed to systematically review, appraise, and evaluate neural AI algorithms employed and their comparative efficacy to conventional methods in endodontic diagnosis and treatment planning. The present research question focused on the literature search about different AI algorithms and models of AI assisted endodontic diagnosis and treatment planning. The search engine included databases such as Google Scholar, PubMed, and Science Direct with search criteria of primary research paper, published in English, and analyzed data on AI and its role in the field of endodontics. The initial search resulted in 785 articles, exclusion based on abstract relevance, animal studies, grey literature and letter to editors narrowed down the scope of selected articles to 11 accepted for review. The review data supported the findings that AI can play a crucial role in the area of endodontics, such as identification of apical lesions, classifying and numbering teeth, detecting dental caries, periodontitis and periapical disease, diagnosing different dental problems, helping dentists make referrals, and also helping them make plans for treatment of dental disorders in a timely and effective manner with greater accuracy. AI with different models or frameworks and algorithms can help dentists to diagnose and manage endodontic problems with greater accuracy. However, endodontic fraternity needs to provide more emphasis on the utilization of AI, provision of evidence based guidelines and implementation of the AI models.

Introduction: Bruxism remains a diagnostic challenge, with no consistently reliable clinical approaches available to document the condition with satisfactory accuracy. This study aimed to incorporate a biosensor device into a conventional bite-night guard to detect bruxism in an in vitro setting.Methods: A sandwich-layering process was used to integrate stress and vibration sensors into an acrylic occlusal stabilization splint. The system included a microcontroller, control unit, and data acquisition module. Occlusal force signals were processed using artificial intelligence-based algorithms. A total of 200 repeated trials were conducted to evaluate system performance. Accuracy, sensitivity, and specificity were calculated as validation metrics.Results: The biosensor prototype demonstrated reliable performance across a force range of 274–700 N. Quantitative evaluation of the neural network yielded an accuracy of 91%, sensitivity of 88%, and specificity of 90% in distinguishing occlusal force thresholds.Conclusion: The findings confirm the feasibility of integrating biosensors within an intraoral appliance for bruxism detection in vitro. Future research should explore long-term durability testing in moist environments and conduct in vivo trials to validate clinical performance.

Background: Endodontic retreatment involves the removal of gutta-percha and sealer from root canals to address treatment failures and persistent infections. This study aimed to systematically evaluate and compare the effectiveness of different gutta-percha removal techniques.Methods: Sixty extracted human teeth with single canals were selected. The canals were initially treated, obturated with gutta-percha, and divided into six groups (n=10 each). Each group represented a distinct removal technique: rotary instrument-driven, Gates-Glidden drill-assisted, solvent-based dissolution, ultrasonic removal, heat-based softening, and a control group. Gutta-percha mass and canal wall cleanliness were assessed post-removal. Statistical analyses were performed using ANOVA and post hoc Tukey's HSD tests.Results: The solvent-based dissolution technique exhibited the most efficient removal, achieving the lowest mean remaining gutta-percha mass (0.89 ± 0.15 mg) and the highest canal wall cleanliness (95% ± 3%). The ultrasonic technique also showed effective removal capabilities with a mean remaining mass of 1.56 ± 0.22 mg and a cleanliness of 89% ± 4%. The rotary technique resulted in a mean mass of 2.47 ± 0.30 mg and cleanliness of 84% ± 5%. Gates-Glidden drill-assisted and heat-based techniques showed moderate performance with remaining masses of 3.18 ± 0.25 mg and 2.10 ± 0.20 mg, respectively, and cleanliness percentages of 78% ± 6% and 81% ± 5%. The control group had the highest remaining mass (9.88 ± 0.42 mg) and the lowest cleanliness (10% ± 2%), confirming the efficacy of the removal techniques.Conclusion: The solvent-based dissolution technique demonstrated superior efficacy in gutta-percha removal. Ultrasonic and rotary techniques were also effective choices. Clinicians should consider these findings when selecting gutta-percha removal methods for endodontic retreatment procedures.Keywords: Endodontic retreatment; Gutta-Percha removal; Canal wall cleanliness; Comparative efficacy; Removal techniques

Aim: The purpose of this ex-vivo study is to evaluate the efficacy of three irrigation techniques in the reduction of E. faecalis in root canal. Materials and Methods: Eighty healthy maxillary anteriors were employed in this investigation. The bacteria E. faecalis was left on teeth for 7 days while they were kept. Once teeth were contaminated, they were randomly divided into three groups of 20 for experimentation and a control group of 20 for comparison. NaviTip FX was used to irrigate Group I, the Max-I-probe was used to water Group II, and the Endovac system was used to water Group III. The number of colony forming units (CFUs) was determined by growing bacteria from root canal samples for 2 days in Brain heart infusion agar after chemo-mechanical operations. Results: There was a substantial decrease in bacterial numbers across all experimental groups compared to group IV (control). Group III (Endovac) had the fewest bacterial colonies among the test groups. There were no discernible changes between Group I (the Navitip FX) and Group II (the Max I probe). Conclusion: Endovac was the most effective of the three irrigation methods for reducing CFUs. This study’s findings lend credence to the idea that the apical negative pressure approach has more potential than the conventional irrigation delivery system for achieving an enhanced antibacterial impact.