Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-cancerous cells to find the best combination of parameters in CNN to predict lung cancer accurately. The proposed system recorded the highest accuracy of 92.79%. In addition to that, the paper addresses 192 observations made using the CNN model.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreObjective(s): To determine the impact of psychological distress in women upon coping with breast cancer.
Methodology: A descriptive design is carried throughout the present study. Convenient sample of (60) woman with breast cancer is recruited from the community. Two instruments, psychological distress scale and coping scale are developed for the study. Internal consistency reliability and content validity are obtained for the study instruments. Data are collect through the application of the study instruments. Data are analyzed through the use of descriptive statistical data analysis approach and inferential statistical data analysis approach.
Results: The study findings depict that women with breast cancer have experien
... Show MoreObjective: This study aims to assess the efficacy of CT-guided true-cut biopsy as a less invasive and cost-effective diagnostic technique for peripherally placed lung lesions. Methods: fourty patients with solitary lung nodule were involved in this study, true cut biopsies under Ct guide was taken then processed for routine H&E staining. Results: different pathological features can be identified with different pathological features giving primary diagnostic screening for lung cancer Conclusion: CT guided thoracic lesion biopsy is very efficient, cost-effective and less invasive technique when compared with the thoracic surgery
Objective: This study aims to assess the efficacy of CT-guided true-cut biopsy as a less invasive and cost-effective diagnostic technique for peripherally placed lung lesions.
As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie
... Show MoreHome Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad
... Show MoreThe current research aims to analyze the mathematics book for the first intermediate grade according to the dimensions of mathematical power by answering the following question: What is the percentage of the availability of the dimensions of mathematical power included in the content of the mathematics textbook for first-grade students, average, in its first, and second parts for the academic year 2020-2021, approved by the Iraqi Ministry of Education / General Directorate of Curricula? The research community was determined by middle school mathematics books, and middle school students for middle ,and high school day schools affiliated to the Directorate of Education in Dhi Qar, and by the intentional test, the research sample was s
... Show MorePrograms and performance budget represents a sophisticated method of public budget numbers, which includes all allocations to be determined for each job or activity within a government entity, which is analyzed according to their needs and costs, and this method can be applied using one of the cost accounting techniques, which is the technique of analyzing the value chain that reduces costs by avoiding activities that do not add value and enhance activities that add value to the economic entity, the current research aims to develop the budget system in government entity by using the budget of programs and performance as a tool for planning and monitoring events and activities, thereby reducing the waste of public money by reducing unnecessa
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