تشغل الفضاءات الداخلية الطبية اهتمام واسع , لما توفره من رعاية صحية للمرضى ,فلابد ان يُهتَمْ بها من الجانب الوظيفي(الادائي), لتحقيق الراحة البصرية والنفسية والجسدية لغرض الوصول الى الاداء الجيد للكادر الطبي, ولهذا وجد ضرورة التعرف على تلك الفضاءات الداخلية بشكل اعمق , وهل انها ملاءمة للمرتكزات التصميمية المتعارف عليها؟ , لذلك تم تسليط الضوء على الفضاءات الداخلية للمختبرات الطبية, وقد تناول البحث المشكلة واهميتها والهدف وتحديد المصطلحات, وشمل الإطار النظري مبحثين، فتناول المبحث الأول الشكل وخصائصه والعناصر المعرفة للفضاء الداخلي وأما المبحث الثاني فهو التنظيم الشكلي في الفضاء الداخلي للمختبرات الطبية والعناصر البصرية, أما إجراءات البحث فقد اعتمد البحث المنهج الوصفي في تحليل العينة عن طريق استمارة التحليل التي شملت محاور نتجت عن مؤشرات الاطار النظري , وقد تم اختيار عينة البحث بشكل قصدي, وفي نهاية الدراسة البحثية يتم عرض اهم النتائج والاستنتاجات والتوصيات والمقترحات , ومن ابرزالنتائج البحثية للدراسة الحالية :
This study aims to Statement of the relationship between Total Quality Management philosophy and Organizational performance from the point of view of the internal customer. A comparison has been made between two companies, one of which applies the requirements of TQM well and the other does not apply these requirements as the (General Company for Electrical Industries/ Diyala) and (General Company for Electrical Industries/ Baghdad) to conduct the search, During the questionnaire prepared for this purpose and distributed to a sample of 30 employees in the General Company for Electric Industries/ Diyala and (20) employees of the General Company for Electrical Industries/ Baghdad. Their answers were analyzed using a simple correlation coef
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreThe growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co
... Show MoreKidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati
Background: Medical students often face substantial psychological stress, which can increase the risk of substance use, professional detriment, and insufficient patient care. However, substance use in medical students remains understudied in Iraq. This study highlights the prevalence, patterns, risk factors, and negative effects of substance use among medical students at the University of Baghdad. A cross-sectional study involving 414 medical students at the University of Baghdad was conducted. The questionnaire included sociodemographic variables and the Alcohol, Smoking, and Substance Involvement Screening Test to screen for psychoactive substance use. The lifetime prevalence of substance use was 38.9%. Among substance users, 42.8
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