Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence

Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study

Background

The healthcare landscape is rapidly evolving, with artificial intelligence (AI) emerging as a transformative force. In this context, understanding the viewpoints of nursing professionals regarding the integration of AI in future nursing care is crucial.

Aims

This study aimed to provide insights into the perceptions of nursing professionals regarding the role of AI in shaping the future of healthcare.

Methods

A cohort of 23 nursing professionals was recruited between April 7, 2023, and May 4, 2023, for this study. Employing a thematic analysis approach, qualitative data from interviews with nursing professionals were analyzed. Verbatim transcripts underwent rigorous coding, and these codes were organized into themes through constant comparative analysis. The themes were refined and developed through the grouping of related codes, ensuring an authentic representation of participants' viewpoints.

Results

After careful data analysis, ten key themes emerged including: (I) Perceptions of AI readiness; (II) Benefits and concerns; (III) Enhanced patient outcomes; (IV) Collaboration and workflow; (V) Human-tech balance: (VI) Training and skill development; (VII) Ethical and legal considerations; (VIII) AI implementation barriers; (IX) Patient-nurse relationships; (X) Future vision and adaptation.

Conclusion

This study provides valuable insights into nursing professionals' perspectives on the integration of AI in future nursing care. It highlights their enthusiasm for AI's potential benefits while emphasizing the importance of ethical and compassionate nursing practice. The findings underscore the need for comprehensive training programs to equip nursing professionals with the skills necessary for successful AI integration. Ultimately, this research contributes to the ongoing discourse on the role of AI in nursing, paving the way for a future where innovative technologies complement and enhance the delivery of patient-centered care.

Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study

INTRODUCTION

The utilization of artificial intelligence (AI) and machine learning (ML) models has brought about a significant transformation in the manner in which periodontists gather information, evaluate associated risks, develop diverse treatment alternatives, anticipate and diagnose dental conditions that compromise periodontal health. The principal objective of this prospective study was to examine periodontists' understanding and acceptance of the application of AI in the realm of periodontology.

MATERIALS AND METHODS

This observational study was conducted on 275 participants based on questionnaire using Google Forms. These forms were pre-validated and subsequently circulated among periodontists in Maharashtra via various social media platforms. The study, in its entirety, comprised four open-ended questions on participants' demographics and 14 closed-ended questions, all of which were presented to the participants in English. These questions aimed to elicit participants' awareness, knowledge, attitudes, and perspectives regarding emerging applications of AI in the field of periodontology. To analyze the collected data, researchers employed the widely utilized Statistical Package for Social Sciences (SPSS) version 22.0.

RESULT

A 75% response rate was achieved and 68% of the respondents were female. 62% periodontists were aware of AI; however, only 24% were aware of its working principles. Most respondents agreed with the use of AI in periodontal diagnosis; however, they disagreed with the use of AI in predicting clinical attachment loss (69%). 80-82% respondents felt that AI should be a part of postgraduate training and should be implemented in clinical practice. However, most periodontists do not use AI for diagnostic or research purposes. 49% periodontists felt that AI does not have better diagnostic accuracy than periodontists, and therefore cannot replace them in the future.

CONCLUSION

Most periodontists possessed a reasonable level of understanding regarding the utilization of AI in the domain of periodontology and expressed a desire to incorporate it into their diagnostic and treatment planning processes for periodontal conditions. Additional endeavors must be undertaken to enhance periodontists' awareness concerning the effective implementation of AI within their professional practice, with the aim of facilitating personalized treatment planning for their respective patients. It is postulated that the integration of AI will augment the likelihood of achieving favorable outcomes within the realm of periodontology.

Comparing the effectiveness of water flosser and dental floss in plaque reduction among adults: A systematic review

Introduction

Interdental aids such as dental floss and water flossers have been found to be effective in removing interdental plaque. This systematic review aimed to compare the available data on the efficacy of dental floss and water flossers in plaque removal among adults.

Materials and Methods

Five databases: PubMed, Scopus, Cochrane, ScienceDirect, Lilac, and Google Scholar were searched from January 1, 2002, to October 31, 2022, to obtain the relevant articles. Based on the search strategy, the titles of the studies were screened independently by two reviewers. Randomized controlled trials were included in the review, in which the study participants were given either dental floss or water flosser. Reduction in plaque scores was the outcome that was assessed. Seven articles met the eligibility criteria and were further processed for qualitative analysis.

Results

The majority of the studies favored water flossers over dental floss in plaque reduction. Water flosser was also found to be effective in removing plaque from inaccessible interproximal areas of the tooth surfaces as compared to dental floss.

Conclusion

Based on the scope of this review, results suggest that water flossers can be used as an effective alternative to dental floss in patients with manual dexterity, patients undergoing orthodontic treatment, and patients with dental prostheses.

Retracted: Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence

[This retracts the article DOI: 10.1155/2022/6505672.].

The Impetus of Artificial Intelligence on Periodontal Diagnosis: A Brief Synopsis

The current advances in digitized data additions, machine learning and computing framework, lead to the swiftly emerging concept of "Artificial Intelligence" (AI), that are developing into areas that were formerly contemplated for human expertise. AI is a relatively rapid paced mechanics wherein the computer technology is tuned to perform human tasks. An auxiliary domain of AI is machine learning (ML), and Deep learning, a subclass of ML technique comprehends multi-layer mathematical operations. AI-based applications have tremendous potential to improve and systematize patient care thereby alleviating dentists from laborious regular tasks, and facilitate personalized, predictive and preventive dentistry. In the dental clinic, AI can execute a variety of easy tasks with greater accuracy, minimal manpower, and with fewer mistakes over human equivalents. These tasks range from appointment scheduling and coordination to helping with clinical evaluation and therapy. Besides, this could assist in the early diagnosis of dental and maxillofacial abnormalities like periodontal ailments, root caries, bony lesions, and facial malformations in addition to automatically identifying and classifying dental restorations on digital radiographs. This brusque narrative review describes the AI-based systems, their respective applications in periodontal diagnosis, the multifarious studies, possible limitations and the predictable future of AI-based dental diagnostics and treatment planning.