Predicting vitamin D deficiency using optimized random forest classifier.

BACKGROUND: Vitamin D can be acquired from various dietary sources, but exposure to sunlight's ultraviolet rays can convert a natural compound called ergosterol present in the skin into vitamin D. AIM: The current study aimed to investigate vital parameters and use an optimized random forest (OptRF) classifier to understand better and predict the effect of environmental and nutritional factors of Vitamin D deficiency. METHODS: A predictive, cross-sectional, and correlational design was utilized in a study involving 350 male and female Tabuk citizens in Saudi Arabia. The Weka machine-learning tool was employed for comprehensive data analysis, with the OptRF algorithm being tailored through advanced feature selection methods and meticulous hyperparameter tuning. RESULTS: In addition to the OptRF classifier, a number of traditional machine learning techniques have been tested and compared on the dataset of vitamin D to analyze and build the predictive model for classifying vitamin D deficiency. In general, the OptRF-based predictive model can statistically describe data for determining significant features related to Vitamin D deficiency. OptRF demonstrated its ability to classify vitamin D deficiency cases with high accuracy 91.42 %. CONCLUSION: This study showed that Tabuk citizens are at high risk of vitamin D deficiency especially among females (gender predictor) with little regard to age, income, smoking, and sun exposure. In addition, exercise, less Vitamin D intake, and less intake of Calcium are also predictors of Vitamin D deficiency. Due to the link between Vitamin D Deficiency and major chronic illnesses, it is important to emphasize the importance of identifying risk factors and screening for Vitamin D Deficiency. It may be appropriate for nutritionists, nurses, and physicians to promote community awareness about strategies to improve dietary Vitamin D intake or consider recommending supplements.

Measuring Awareness of Infection Control Guidelines for Patients with COVID-19 in Radiology Departments in Saudi Arabia.

Due to the contagious nature of the COVID-19 virus, healthcare workers are at a great risk of infection. Since medical imaging plays a significant part in the healthcare system and is often used in the diagnosis of potential COVID-19 patients, the radiology personnel are at a very high risk of becoming infected. PURPOSE: This study aims to assess the enforcement of infection control guidelines for patients with COVID-19 during medical imaging procedures and raise awareness of infection control in different hospitals in Saudi Arabia. METHODS: A total of 128 responses were collected from four hospitals across Saudi Arabia using a new structured questionnaire, which was created for health workers by the WHO specifically for this purpose. Data were collected during the COVID-19 pandemic in April 2020. RESULTS: Most participants correctly followed the guidelines of the WHO and Centers for Disease Control and Prevention (CDC) on infection control in the X-ray and general radiology departments. Guideline awareness was higher among magnetic resonance imaging (MRI) and computerised tomography (CT) radiographers, which reduced the risk of future infections. Out of the total respondents, 98.4% stated that they had received formal training in hand hygiene. Only 40.6% of participants, however, knew that respiratory droplets are the primary mode of transmission of the virus from person to person. CONCLUSION: The knowledge of healthcare professionals in the radiology department regarding infection control needs to be continually assessed. A focus on educational interventions on infection control is required in order to maintain well-informed medical staff.

Comparison between MCNP5, Geant4 and experimental data for gamma rays attenuation of PbO-BaO-B2O3 glasses.

Monte Carlo simulations, MCNP5 and Geant4 codes were developed to investigate radiation shielding properties of xPbO-(50-x) BaO-50B2O3 (where 5 ≤ x ≤ 45 mol%) consider to be glass systems. The mass attenuation coefficients were evaluated for different PbO concentration in the glass samples for varies photon energies of 0.356, 0.662, 1.173 and 1.332 MeV. The obtained mass attenuation coefficient values used to calculate half-value layer, effective atomic number, and electron density. The simulation parameters were compared with experimental data. Results show that the simulation results of mass attenuation coefficients for all PbO concentrations were generally in good agreement with experimental results, however, mass attenuation coefficient values calculated using Geant4 were slightly lower than MCNP5 and experimental data on the low energy of 0.356 MeV. The results obtained from MCNP5 and Geant4 codes might be able to assessment mass attenuation for different glass systems. Furthermore, gamma ray, fast neutron and charged particle interaction for the glass systems were studied using buildup factors, fast neutron removal cross sections and ranges respectively.

Leadership styles' influence on the quality of nursing care.

PURPOSE: The purpose of this paper is to investigate managers' leadership styles, from the perspective of registered nurses, and its effects on the quality of nursing care in both the private and public healthcare sectors. An additional aim is to assess the relationship between leadership styles and particular organisational outcomes. DESIGN/METHODOLOGY/APPROACH: The sample for this quantitative research study was comprised of 400 respondents, among which 50 were nurse managers, 150 were staff nurses and the remaining respondents were patients. Two questionnaires were used in this study: the multi-factor leadership questionnaire (MLQ) 5X short and a patient satisfaction with nursing care quality questionnaire (PSNCQQ). FINDINGS: A positive correlation was found between the transformational leadership style with leadership outcomes and the quality of nursing care (r=0.811**, 0.759**, 0.789** and 0.877** for extra effort, job satisfaction, leader effectiveness and quality, respectively). PRACTICAL IMPLICATIONS: Although the sample study was extensive, a possible limitation is that the research utilised convenient sample who are working in the private and public healthcare sectors thus limiting the generalisability of the study. ORIGINALITY/VALUE: This study was proposed as a baseline for upcoming studies in areas of education, nursing practice, research and quality. Moreover, this study was expected to be imperative to the hospital's management, in order to improve the current level of leadership, education models and advancement programs for the healthcare sector's senior staff.