ABSTRACT
Background: Dental caries is a prevalent oral health issue, often diagnosed through intraoral radiographs. The accuracy of Artificial Intelligence (AI) in diagnosing dental caries from these radiographs is a subject of growing interest. Materials and Methods: In this RCT, 200 intraoral radiographs were collected from patients seeking dental care. These radiographs were independently evaluated by both AI-based software and experienced human dentists. The software utilized deep learning algorithms to analyze the radiographs for signs of dental caries. The performance of both AI and human interpretations was compared by calculating sensitivity, specificity, and overall accuracy. Arbitrary values of 85% sensitivity, 90% specificity, and 88% overall accuracy were set as benchmarks. Results: The AI-based software demonstrated a sensitivity of 88%, a specificity of 91%, and an overall accuracy of 89% in diagnosing dental caries from intraoral radiographs. Human interpretation, however, yielded a sensitivity of 84%, a specificity of 88%, and an overall accuracy of 86%. The AI-based software performed consistently close to or above the predefined benchmarks, while human interpretation showed slightly lower accuracy rates. Conclusion: This RCT suggests that AI-based software is a valuable tool for diagnosing dental caries from intraoral radiographs, with performance comparable to or exceeding that of experienced human dentists. The consistent accuracy of AI in this context highlights its potential as an adjunctive diagnostic tool, which can aid dental professionals in more efficient and precise caries detection.
ABSTRACT
Background: Endodontic flareups are always very difficult to treat because of reasons like drug resistance previously sodium hypochlorite and chlorhexidine have been used in the literature but with advancements newer materials like herbal products have been tried for this purpose. Thus, present vitro study was conducted to comparatively evaluate the efficacy of herbal formulations on commensals of oral cavity and root canal. Materials and Methods: In this in vitro study antimicrobial efficacy of chlorhexidine 2%, Septilin and Triphala wer evaluated with the help of Kirby Bauer test. The microorganisms used were Staphylococcus aureus and Escherichia coli. The samples were placed in standardized wells and were subjected to incubation. Subsequently zones of inhibition were measured with the help of a caliper. One-factor analysis of variance, Tukey's least significant difference post hoc test and Student's independent t-test were performed to find a significant difference (P < 0.05) in the two groups. Results: For chlorhexidine in S. aureus mean antibacterial efficacy was 11.10 ± 1.25 and in E. coli 10.0 ± 1.33. The value for S. aureus was lesser in Triphala with a value of 10.35 ± 1.63 and in E. coli mean value was 9.05 ± 1.27. For Septilin the mean for S. aureus was 10.40 ± 1.04, and the mean antibacterial efficacy in E. coli was 9.65 ± 1.38. Conclusion: Septilin and Triphala showed remarkable efficacy concerning zones of inhibition. These herbal formulations have tremendous potential to be used as adjuncts to traditional disinfection modalities though it has scope of further research.
