Knowledge and Attitude of Undergraduate Health Professions Students towards Hepatitis B and C.

The current study sought to establish the attitude and knowledge level of medical science students in Tibah University towards hepatitis B and C. A cross-sectional study involving 369 students drawn from the faculties of medicine, dentistry, applied medical sciences, pharmacy, nursing, and medical rehabilitation sciences was conducted where a standardised questionnaire was used to determine the attitude and knowledge level of undergraduate students drawn from the college of medicine in Tibah University, Saudi Arabia, regarding viral infections. With a mean of 0.71, 0.69, and 0.66 and a standard deviation (SD) of 0.24, 0.34, and 0.24 for virology and transmission, symptoms and clinical outcomes, and treatment and prevention, respectively, the knowledge level of the health professions students towards hepatitis B and C infections was significant. The knowledge level about the infections was higher among male students than among female students. Similarly, students in their final years of medical school had significantly higher knowledge levels about hepatitis B and C than their counterparts in their first years of medical school. There was also a positive correlation between the attitude of the health professions students towards the disease and their knowledge levels of the disease. Findings indicate that enhanced instruction on the nature, virology, transmission, symptoms, treatment, clinical outcomes, and prevention of hepatitis B and C can help improve the knowledge levels and attitude of the health professions students towards the disease and its management.

Parameter free AEWMA control chart for dispersion in semiconductor manufacturing.

The study presents a new parameter free adaptive exponentially weighted moving average (AEWMA) control chart tailored for monitoring process dispersion, utilizing an adaptive approach for determining the smoothing constant. This chart is crafted to adeptly detect shifts within anticipated ranges in process dispersion by dynamically computing the smoothing constant. To assess its effectiveness, the chart's performance is measured through concise run-length profiles generated from Monte Carlo simulations. A notable aspect is the incorporation of an unbiased estimator in computing the smoothing constant through the suggested function, thereby improving the chart's capability to identify different levels of increasing and decreasing shifts in process dispersion. The comparison with an established adaptive EWMA-S2 dispersion chart highlights the considerable efficiency of the proposed chart in addressing diverse magnitudes of process dispersion shifts. Additionally, the study includes an application to a real-life dataset, showcasing the practicality and user-friendly nature of the proposed chart in real-world situations.

Risk adjusted EWMA control chart based on support vector machine with application to cardiac surgery data.

In the current study, we demonstrate the use of a quality framework to review the process for improving the quality and safety of the patient in the health care department. The researchers paid attention to assessing the performance of the health care service, where the data is usually heterogeneous to patient's health conditions. In our study, the support vector machine (SVM) regression model is used to handle the challenge of adjusting the risk factors attached to the patients. Further, the design of exponentially weighted moving average (EWMA) control charts is proposed based on the residuals obtained through SVM regression model. Analyzing real cardiac surgery patient data, we employed the SVM method to gauge patient condition. The resulting SVM-EWMA chart, fashioned via SVM modeling, revealed superior shift detection capabilities and demonstrated enhanced efficacy compared to the risk-adjusted EWMA control chart.