Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

Objective(s): Biocompatibility, non-toxicity, minimal allergenicity, and biodegradability are all characteristics of chitosan. Other biological properties of chitosan have been reported, including antitumor, antimicrobial and antioxidant activities. This research aim is the synthesis of drug compounds by preparation and characterization of polymer chitosan Schiff base and chitosan Schiff base / Poly vinyl alcohol / poly vinyl pyrrolidone Nanocomposite and study applications (anticancer cell line, antimicrobial agents). Methods: Chitosan Schiff base was prepared from the reaction of chitosan with carbonyl group of 4-nitro benzaldehyde. Polymer blend have been prepared by solution casting method. Chitosan Schiff base mixing with PVA and PVP

This cross-sectional, questionnaire-based study evaluated the knowledge, attitude and practice towards breast cancer and breast self-examination [‎BSE]‎ among 387 [‎302 females and 85 males]‎ educated Iraqis affiliated to 2 Iraqi universities. The participants were categorized into 3 occupations: student [‎71.3%]‎, teaching staff [‎10.3%]‎ and administrative staff [‎18.3%]‎. About half of the participants had a low knowledge score [‎< 50%]‎; only 14.3% were graded as [‎Good]‎ and above. Almost 75% of the participants believed that the best way to control breast cancer was through early detection and other possible preventive measures. Most participants [‎90.9%]‎ had heard of BSE, the main source of informatio

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

الخلفية: إن سمية الدواء والآثار الجانبية للعلاج الكيميائي تؤثر سلبا على مرضى سرطان الثدي. الأهداف: لتقييم فعالية التدخلات الصيدلانية في تحسين معرفة مرضى سرطان الثدي ومواقفهم وممارساتهم فيما يتعلق بالعلاج الكيميائي لسرطان الثدي.