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 med

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

Objective(s) : This study aimed at evaluating the seroprevalence of anti -HCV and studying the
correlation between hemophilia and risk factors for acquiring HCV such as age , marital status &
occupation among hemophilic patients .
Methodology : 210 hemophilic patients in children welfare teaching hospital/medical city/Baghdad–Iraq
(hemophilia center) were investigated using prepared questionnaire and tested for HCV infection, those
were measuring patient’s age, hemophilia types and severity, marital status, residency and history of
previous HCV infection .
Results : Most hemophilic patients were hemophilia A at severe , hemophilia was at age group 20 – 29
years , the majority of patients were unmarried a

The research aims to know the reverberation of the the electronica news bulletin of the ministry of higher education and scientific research  in the newspapers of: (AL-Taakhi, AL-Zaman, ALAdala,AL-Sabah and Baghdad) for period from 2^nd October 2011 to 1^st November 2011 to explain its activity and advantage for the other newspapers and to show the importance which the newspapers showed for the study of the news subject in the bulletin, as well as,to show the proportional differences in which the newspapers interested in the subjects of the published news, and to reach to the results which lead us to good conclusions for the service of decision owner and open new horizons for the researchers to expanding in the s

The members of the family of Eentrobacteriaceae harbour a gene cluster called polyketide synthase (pks) island. This cluster is responsible for the synthesis of the genotoxin colibactin that might have an important role in the induction of double-strand DNA breaks, leading to promote human colorectal cancer (CRC). Eleven out of the eighty eight isolates (12.5%) were pks+, distributed as 7 (8%) isolates of E. coli, 2 (2.25%) of K. pneumoniae and 2 (2.25%) of E. aerogenes. The cytotoxic effects of selected pks+ isolates (E. coli and E. aerogenes) on HeLa cells were represented by decreasing cell numbers and enlarged cell nuclei in comparison to the untreated cells. Cyt

Evolution has become a feature of this era because of the speed that makes it open multiple horizons and many to identify everything that is new in different areas and also characterized by the competitive position of emotional attitudes changing depending on the positions of winning and defeat, and the use of training methods are the most important pillars of the game of wrestling, The methods contribute to raising the level of the wrestler and refining his physical and skill potential. The problem of the research is that the shooting exercises from above the chest are very important in Roman wrestling and can be terminated by the player. Through very personal interviews for coaches and concluded that there is a weakness in the level of fl

The study aimed to determine the impact of energy for the north and south magnetic poles on the the growth of bacteria isolated from cases of tooth decay, 68 swabs were collected from surfaces of faulty tooth, the detected of Staphylococcus aureus