Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze medical images with favorable results. It can help save lives faster and rectify some medical errors. In this study, we look at the most up-to-date methodologies for medical image analytics that use convolutional neural networks on MRI images. There are several approaches to diagnosing and classifying brain cancers. Inside the brain, irregular cells grow so that a brain tumor appears. The size of the tumor and the part of the brain affected impact the symptoms.
Objective: To evaluate nurses' practices concerning isolation techniques for Adult Leukemic Patients (ALP).
Methodology: A descriptive study was carried out at the isolation rooms at leukemic wards in Baghdad Teaching
Hospitals, starting from Jan. 27th 2008 up to the 27th of Apr. 2008. To achieve the objectives of study, a non-probability
"purposive" sample of (50) nurse was selected out of four Teaching Hospitals in Baghdad city were selected according
to the criteria of the study sample.
The study instrument consisted of two major parts. It is based on the review of literature. First is concerned with
demographic data for nurses; and the second part is observational tool (checklist) is composed of (83) item. The conte
Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i
... Show MoreThis paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi
... Show MoreThis study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
... Show MoreRoller Compacted Concrete is a type of concrete that is environmentally friendly and more economical than traditional concrete. Roller Compacted Concrete is typically used for heavy-duty and specialist constructions, such as hydraulic structures and pavements, because of its coarse surface. The main difference between RCC and conventional concrete mixtures is that RCC has a more significant proportion of fine aggregates that allow compaction and tight packing. In recent years, it has been estimated that several million tons of waste demolished material (WDM) produced each year are directed to landfills worldwide without being recycled for disposal. This review aimed to study the literature about creating a Roller-Comp
... Show MoreIn the current study, remote sensing techniques and geographic information systems were used to detect changes in land use / land cover (LULC) in the city of Al Hillah, central Iraq for the period from 1990 - 2022. Landsat 5 TM and Landsat 8 OLI visualizations, correction and georeferencing of satellite visuals were used. And then make the necessary classifications to show the changes in LULC in the city of Al Hillah. Through the study, the results showed that there is a clear expansion in the urban area from 20.5 km2 in 1990 to about 57 km2 in 2022. On the other hand, the results showed that there is a slight increase in agricultural areas and water. While the arid (empty) area decreased from 168.7 km 2 to 122 km 2 in 2022. Long-term ur
... Show MoreBackground: The pandemic crisis prompted the world to adopt unexpected approaches to continue life as normally as possible. The education sector, including professors, students, and the overall teaching system, has been particularly affected. Objective: This study seeks to evaluate the benefits, challenges, and strategies related to COVID-19 from the perspectives of college students, particularly those in higher education in Iraq. Method: The online survey questionnaire was distributed via Google Forms and specifically aimed at undergraduate dental students. Results: A total of 348 students participated in the survey. There was a significant correlation (P > 0.01) between student satisfaction with hybrid learning and their experi
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