Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

Background: Corona virus disease 2019 (COVID-19) is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, leading to an ongoing pandemic.

Aim of study: to review the clinical, lab investigation and imaging techniques, in pediatric age group affected COVID-19 to help medical experts better understand and supply timely diagnosis and treatment.

Subjects and methods: this study is a retrospective descriptive clinical study. The medical records of patients were analyzed. Information’s recorded include demographic data, exposure history, symptoms, signs, laboratory findin

The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the

Objectives: This study aimed to evaluate the performance of staff nurses at primary health care centers in Baghdad city and to compare them with their demographic characteristics of age, gender and education.
Methodology: A descriptive design was carried out at Baghdad City’s primary health care centers from January 2nd 2019 to May 1st 2020. An instrument was developed for the purpose of the study. A non-probability, multi-stage purposive sample of (52) staff nurses was recruited from nurses working at primary health care centers in Baghdad City. The instrument is used to evaluate staff nurses’ performance which includes (62) items. These items are divided to (13) main domains related to evaluation of work quantity, work quality,

Objective: To evaluate the client's satisfaction about the services provided in primary health care centers in the
city of Baghdad and its impact on the improvement of services.
Methodology: A simple random sample consisting of (200) clients to primary health care centers in the city of
Baghdad, (15-20) clients for each center using a questionnaire to evaluate the client's satisfaction for the service
and the use of the direct method of interview, which lasts for (6-10) minutes.
Results: Results of the study show that the number of men visits to primary health care centers, fewer women
This indicates that the most important responsibilities of family members and private health care is the
responsibility of women than

Background: Pregnancy is a stressful state of increased inflammatory activity, and pregnancy – associated hormone changes can influence periodontal tissues, these inflammatory activity lead to production of inflammatory mediators. Interleukin 1 beta (IL-1β) is a potent pro-inflammatory cytokines that is consistently associated with periodontal diseases. This study was designed to determine the periodontal health status and detect the serum level of IL-1β in the healthy pregnant women at first, second and third trimester and compare it with healthy non pregnant women, and determine its correlation with different clinical periodontal parameters. M