1,720,988 research outputs found
Comprehensive Evaluation of Computerized Information Systems in Enhancing Nursing Practice and Clinical Decisions
Get PDFNursing practice has been revolutionized by the incorporation of computerized health information systems into clinical settings, which have improved workflow efficiency, supported evidence-based decision-making, and improved patient data management. The efficacy in enhancing clinical decision-making and nursing practice requires a thorough assessment. The purpose of the research is to examine how computerized health information systems affect clinical decision-making, patient safety, and nursing workflows while identifying critical elements that affect efficacy in various healthcare settings. A comprehensive survey with an emphasis on system usability, integration into clinical processes, and perceived influence on patient outcomes was administered to 210 registered nurses from different hospital units. To achieve a comprehensive assessment, a mixed-method approach was used, combining qualitative observations and quantitative statistical analysis. It examines how computerized health information systems boost multidisciplinary collaboration, increase documentation accuracy, and assist clinical decision-making in real-time. To investigate the connections between system effectiveness, user experience, and clinical performance, descriptive and inferential statistical methods were used, such as regression analysis and structural equation modeling (SEM). Results show computerized health information systems greatly enhance decision support, clinical workflow effectiveness, and documentation accuracy. It emphasizes how crucial computerized health information systems are to contemporary nursing practice. Maximizing the influence of systems on patient care and decision-making requires improving system design, ensuring training is appropriate, and matching features with clinical requirements.
Evaluation of the Alveolar Fossa Microenvironment for Enhancing Tooth Root Regeneration Using Stem Cells
Get PDFThe microenvironment in the alveolar fossa possesses a fundamental significance in tooth root regeneration processes. The behavior of stem cells is directly affected by pH values together with oxygen levels alongside nutritional supplies and scaffolds or growth factors. Research used 47 participants to investigate how different conditions found in the alveolar fossa impact stem cell-based tooth root regeneration through statistical assessment of relevant microenvironmental influences. These factors require optimal adjustment to achieve better therapeutic results in dental tissue engineering. Under laboratory conditions, the cell cultures received different microenvironmental conditions that included three pH levels (6.5, 7.0, and 7.4) together with various oxygen levels and scaffold types. Research used paired t-test procedures to check pre- and post-intervention shifts with ANOVA and subsequent post hoc testing to distinguish between groups together with multiple linear regressions to evaluate collective variables\u27 impact on regeneration results. Research assessed results through measurements of cellular proliferation alongside differentiation signs and tissue regrowth size. Significant differences in stem cell proliferation and differentiation were observed across microenvironmental conditions. Post hoc analysis identified hypoxic conditions combined with scaffold material A as the most conducive for regeneration. Multiple linear regressions indicated that pH and oxygen concentration were the most influential factors, contributing to 65% of the variability in regeneration outcomes. The alveolar fossa microenvironment significantly affects tooth root regeneration. Optimized conditions, particularly hypoxia and neutral pH, enhance stem cell-based regenerative outcomes. These findings offer insights into tailoring microenvironments for clinical applications in regenerative dentistry
Investigation of Online Interactive Modules for Strengthening Emergency Preparedness in Nursing Education
Get PDFThe effective emergency preparedness in nursing education necessitated innovative teaching strategies that strengthened both theoretical knowledge and practical skills. Traditional instruction alone failed to provide nursing students with the critical competencies required for high-pressure emergency scenarios. Research examined the role of online interactive modules in improving emergency response proficiency, focusing on Emergency and Life Support Training (ELST), a web-based multimedia simulation game designed to enhance engagement, motivation, and skill acquisition in emergency care. A controlled investigation was carried out with final-year undergraduate nursing students (N=120) to assess the efficiency of ELST in emergency guidance. The intervention group engaged with ELST before realistic training, while the control group received conventional coaching. Quantitative investigation, performed using SPSS, involved an independent t-test to evaluate group performance, a paired t-test to assess within-group development, and a Chi-square test to analyze categorical differences in competency levels. The findings proved a statistically significant enhancement (p < 0.05) in key emergency competencies, including equipment verification, airway assessment, safe and effective use of a defibrillator, chest compression technique, and emergency medication management. Qualitative comments underscored the profit of interactive learning, as students reported increased confidence, faster decision-making, and better retention of emergency protocols. These results highlighted the potential of integrating simulation-based modules into nursing curricula to improve engagement, reinforce practical skills, and advance preparedness for critical situations. Incorporating digital learning equipment into emergency education bridged the break between academic instruction and real-world submission, finally leading to more capable and confident nursing professionals
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Implementing Sustainable Waste Management Practices in Healthcare Facilities
No full textSustainable garbage management in healthcare centres is important to protect the earth and follow the rules. If medical garbage isn't properly disposed of, it can be very harmful to both people and the earth. This study looks into how sustainable waste management techniques can be used in hospital situations. It focusses on recycling, sorting trash, and using materials that are good for the environment. Researchers used a mix of methods, including in-depth conversations with healthcare workers and statistical analysis of trash production, dumping methods, and the success of green efforts. A number of healthcare facilities were surveyed and waste management practices were directly observed. This was followed by conversations with key players such as hospital managers, environmental officers, and waste removal companies. The data showed that most healthcare facilities had trouble telling the difference between dangerous and non-hazardous waste and weren't aware of any sustainable options. But those that set up organised ways to separate trash, training programs for employees, and relationships with approved recycling companies saw a big drop in the amount of trash going to dumps and better use of resources. The results show that the best ways to make healthcare centres more environmentally friendly are to provide thorough training, have clear rules about how to separate trash, and work together with outside waste management services. In conclusion, using sustainable methods for managing trash is not only possible, but it will also help protect the earth and make healthcare centres run more smoothly
Advanced Predictive Modeling for Hypertension Risk Based on Health Indicators and Machine Learning Technique
Get PDFIntroduction: The condition of hypertension significantly accelerates the incidence of cardiovascular diseases and demands timely and proper measurement of the avoidable risk. Traditional techniques in the measurement of the pressure in the arteries provide accurate figures but are incapable of forecasting the risk of the development of hypertension.Aim: The goal was to establish an Efficient Pelican Optimized Dynamic Random Forest (EPO-DRF) model from health markers to forecast the hypertension probability.Methods: Patient information was extracted from clinical history, such as clinical predictors and lifestyle predictors of hypertension. Preprocessing, such as normalization and cleaning, was carried out to ensure precision and consistency. The significant predictors, such as age, cholesterol, blood sugar, and BMI, were determined. Optimum pelican optimization was used to increase the predictive efficiency by identifying the most significant predictors and removing redundant predictors.Result: To forecast the hypertension probability, the EPO-DRF model also displayed excellent outcomes, such as the F1-score (86.2%), the accuracy (90.4%), the sensitivity (87.5%), and the precision (85.7%). Classification performance and the most significant feature selection also underwent optimization in the course of the optimization to increase the efficacy of the model.Conclusion: The novel methodology arrived at an effective and efficient way to attain hypertension screening at an early stage, in alignment with preventive care practices and minimizing hypertension complications. It also helped healthcare analytics by having a precise predictive model to project future hypertension detection, making timely intervention and enhancing outcomes among the patients
Implementing AI-Driven Diagnostic Tools to Improve Quality of Life Assessments
No full textAbstract: Using artificial intelligence (AI) in the healthcare sector alters doctors' major decision-making process. Evaluating patients' quality of life (QoL) is one area where artificial intelligence seems rather promising. Understanding how various illnesses and therapies influence a person's overall health depends much on quality of life testing. Standard QoL exams, which rely on hand-written assessments and patient comments on their health, have issues like being subjective, biassed, and sluggish when it comes to analyse vast volumes of data. AI-powered testing tools can provide more accurate, quick, scalable methods to evaluate QoL if one is looking for a way around these challenges. This essay examines how artificial intelligence technology could alter the methodology of quality of life surveys. Diagnostics based on artificial intelligence are quite useful. For patient anecdotes, for instance, natural language processing (NLP) may be employed; machine learning techniques can then be used to project QoL values from medical data. AI systems can handle a lot of clinical data including medical records, imaging data, patient-reported results to generate objective, real-time, tailored QoL evaluations consistent and reusable once and again. Furthermore, these instruments can identify early warning indicators of deterioration that would not be evident using more conventional approaches. the usage of several sorts of records sources inclusive of clever tech and cellular fitness apps which increases the accuracy of stories in real time and allows non-stop tracking AI-driven checking out will also be led via This method not handiest courses medical doctors in making better selections however additionally affords people extra manipulate over their fitness, therefore improving their excellent of life over time. The studies additionally addresses moral questions arising from AI-primarily based QoL assessments consisting of data protection, patient permission, and what clinical professionals should do upon assessment of AI outcomes. through discussion of these issues, this take a look at emphasises the need of ensuring that synthetic intelligence generation be applied in a way that complements the interaction among the affected person and company in preference to replaces human know-how.El uso de la inteligencia artificial (IA) en el sector sanitario altera el importante proceso de toma de decisiones de los médicos. La evaluación de la calidad de vida (CdV) de los pacientes es un ámbito en el que la inteligencia artificial parece bastante prometedora. Comprender cómo influyen las distintas enfermedades y terapias en la salud general de una persona depende en gran medida de los exámenes de calidad de vida. Los exámenes https://doi.org/10.56294/hl2023237estándar de calidad de vida, que se basan en evaluaciones escritas a mano y en los comentarios de los pacientes sobre su salud, presentan problemas como la subjetividad, la parcialidad y la lentitud a la hora de analizar grandes volúmenes de datos. Las herramientas de análisis basadas en IA pueden proporcionar métodos más precisos, rápidos y escalables para evaluar la calidad de vida si se busca una forma de superar estos problemas. Este ensayo examina cómo la tecnología de inteligencia artificial podría alterar la metodología de las encuestas de calidad de vida. Los diagnósticos basados en inteligencia artificial son bastante útiles. Para las anécdotas de los pacientes, por ejemplo, se puede emplear el procesamiento del lenguaje natural (PLN); luego se pueden utilizar técnicas de aprendizaje automático para proyectar valores de calidad de vida a partir de datos médicos. Los sistemas de IA pueden manejar gran cantidad de datos clínicos, como historias clínicas, datos de diagnóstico por imagen o resultados notificados por los pacientes, para generar evaluaciones de la calidad de vida objetivas, en tiempo real, adaptadas, coherentes y reutilizables una y otra vez. Además, estos instrumentos pueden identificar los indicadores de alerta temprana de deterioro que no sería evidente el uso de enfoques más convencionales. el uso de varios tipos de fuentes de registros, incluida la tecnología inteligente y aplicaciones de fitness celular que aumenta la precisión de las historias en tiempo real y permite el seguimiento sin parar AI impulsada por la comprobación a cabo también se llevará a través de Este método no cursos handiest médicos en la toma de mejores selecciones, sin embargo, además, ofrece a las personas más manipular sobre su estado físico, por lo tanto, la mejora de su excelente calidad de vida en el tiempo. Los estudios, además, aborda cuestiones morales que surgen de AI-principalmente basado en evaluaciones de calidad de vida que consiste en la protección de datos, el permiso del paciente, y lo que los profesionales clínicos deben hacer tras la evaluación de los resultados de la IA. a través de la discusión de estas cuestiones, este echar un vistazo a hace hincapié en la necesidad de garantizar que la generación de inteligencia sintética se aplica de una manera que complementa la interacción entre la persona afectada y la empresa en lugar de reemplazar a los seres humanos know-how
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