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Knowledge, Attitude, and Practice Study on Cardiovascular Disease Risk Factors in the Mangalore Community
Introduction: Cardiovascular diseases are the leading cause of death in the world, causing 17.9 million deaths annually. In India, with cities like Mangalore included, the burden of cardiovascular disease is increasing rapidly. Methods: A cross-sectional survey was conducted on 215 adults aged 18 years through stratified random sampling. Data collection was accomplished using a validated structured questionnaire; it measured knowledge relating to cardiovascular disease risk factors, attitudes toward prevention, and health practices. High questionnaire reliability was observed; this is because Cronbach's α for the knowledge, attitude, and practice parts appeared to be 0.82, 0.78, and 0.76, respectively. Descriptive statistics, t- t-tests, ANOVA, and multiple regression were used in the analysis. Results: The mean age was 42.3±13.7years, and females were at 51.2%. Awareness that hypertension is a risk factor for cardiovascular disease was 88.4%, 95% CI: 83.9-92.9%. Conversely, awareness of the risk of diabetes was slightly lower, at 72.1%, 95% CI: 65.9-78.3%. The prevention attitude score is positive, with 90.7%, 95% CI: 86.5-94.9% agreeing to exercise regularly. Only 70.0%, 95% CI: 63.7-76.3% agreed to having exercised lately. Education level strongly predicted knowledge scores (β=0.15, p=0.02), and knowledge scores were positively correlated with attitude scores (r=0.45, p
p38α and p38β regulate osmostress-induced apoptosis
The Role of Artificial Intelligence in Dentistry: A Narrative Review
Integration of artificial intelligence in dentistry has transformed the way dental professionals diagnose, plan treatment, and manage patient care. AI technologies, such as machine learning and deep learning, enhance precision, efficiency, and effectiveness in dental practices to produce better outcomes. This review discusses the broad applications of AI in various fields of dentistry, which range from diagnostic imaging, prediction of treatment, restoration care, orthodontic practice, endodontics, and preventive care. In diagnostic imaging, for example, AI-based techniques such as CNNs significantly enhanced the ability to diagnose dental pathologies, for instance, caries, periodontal disease, and oral cancers, most of which are diagnosed at much earlier stages than with traditional approaches. These methods allow for fewer mistakes, better outcomes, and overall, a greater value for predictive modeling, and especially, treatment planning. Predictive modeling and treatment planning, along with outcome-driven analytics, are changing the formulation of prognosis and modeling of treatment, along with algorithms such as ANN. AI is an imperative core for restorative and prosthetic dentistry. Crown and denture design has significantly benefited from generative design algorithms and other automated design tools. Individualized prosthetic dentures and crowns that fit and are comfortable as well as aesthetic have advanced design. These AI tools in orthodontics and endodontics are also augmenting treatment precision by simulating tooth movements and success predictive modeling for techniques like root canals. The improvements that AI can and will offer dentistry as a whole are numerous. The challenge of implementing AI is widespread. Data privacy and the high cost of adopting advanced technologies are the core issues. The full potential of AI can and surely will augment the care of practice in augmenting AI in Dentistry.
An oncoprotein CREPT functions as a co-factor in MYC-driven transformation and tumor growth
Assessing Knowledge, Attitudes, and Practices of Augmented Reality Technology in Dentistry: A Cross-Sectional Survey
Introduction: Augmented Reality (AR) technology is increasingly recognized for its potential to enhance various aspects of dental practice, including treatment planning, patient education, and training. Despite this potential, the understanding of dental professionals' knowledge, attitudes, and practices regarding AR technology remains underexplored. The objective of this research is to examine the experience, perceived advantages, and real application of augmented reality (AR) Technologies of dental faculty and students. Methodology: A sample of 132 dental students, some integrated into the workforce as part-time private dentists, and faculty members of a single dental school, completed a self-administered online survey. Knowledge and application of AR technology in dentistry, and Experience with AR practice, were the constructs of the study. An administered questionnaire, partially digital and partially paper and pencil, was divided into two parts: Knowledge Assessment and Practice Assessment. The survey results were analyzed using reference statistics. Results: Knowledge Assessment respondents confirmed understanding Augmented Reality (AR) technology (69.7), and AR technology in dental training/education was recognized (65.9). 57.6% of the participants in the Practice Assessment declared absence of AR in their educational and/or professional practice, but an AR technology practice was wanted (67.4). The self-rated proficiencies that 44.47% of the respondents professed were in the range of self-score 3 in the application of AR (moderate). A small fraction (16.7) declared their AR application self-score was above the higher order. Conclusion: It can be concluded from this work that AR technology in academic and practical dentistry is vastly underutilized, notwithstanding the high realization and appreciation for its application.