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.
Objective(s): The study aims to identify the role of sociodemographic factors in predicting the level of psychological hardiness of nurses.
Methodology: A descriptive correlational study conducted in the Medical City hospitals in the city of Baghdad during the period from November 1, 2022 to May 1, 2023 on a sample of 156 male and female nurses. The validity of the quest
... Show MoreA synthesis series of new heterocyclic derivatives (A2-A7) (pyrrole, pyridazine, oxazine and imidazol) derived from 4-acetyl-2,5-dichloro-1-(3,5-dinitrophenyl)-1H-pyrrole-3-carboxylate(A1) have been synthesised. Synthesis of compound (A2) by the reaction of starting material (A1) with hydroxyl amine hydrochloride in the presence of pyridine. Compound (A2) was reacted with hydrazine hydrate in dry benzene to give (A3) derivative. The compound )A3( deals with sodium nitrite to give diazonium salt, and the reaction diazonium salt with ethyl acetoacetate to produce compound (A4). To a mixture of compound (A4) and hydroxyl amine with sttired to yield (A5).Compound (A6) was prepared by reaction compound (A4) with thiosemicarbazide in presence
... Show MoreTo assess the impact of COVID‐19 on oral hygiene (OH) awareness, attitude towards dental treatment, fear of infection and economic impact in the Middle East.
This survey was performed by online distribution of questionnaires in three countries in the Middle East (Jordan, Iraq and Egypt). The questionnaire consisted of five sections: the first section was aimed at collecting demographic data and the rest sections used to assess OH awareness, attitude towards dental treatment, degree of fear and economic impact of COVID‐19. The answers were either multiple choice, closed‐end (Yes or N
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreThe present study aims to identify the role of behavioral disorders (anxiety disorder, behavior disorder "behavior", confrontation and challenge disorder, aggressive behavior) in predicting bullying patterns (verbal, physical, electronic, school) in a sample of adolescents with autism spectrum disorder. For this purpose, the researcher developed scales to measure the behavioral disorders and the bullying patterns among adolescents with autism spectrum disorder. The researcher adopted the descriptive survey approach. The study sample consists of (80) adolescents with autism spectrum disorder with ages range from (15-19 years) and (45-53 years old) in association with israr association for people with special needs in the northern borders
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