Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

In this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most

Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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

In the last few years, there have been a lot of changes in the economy, society, and the environment. This has led to much competition between companies, directly and indirectly affecting production and marketing processes. Most companies are trying to cut production and manufacturing costs by using modern cost techniques such as product life cycle costing and Continuous Improvement (Kaizen) technology, in the method of measuring production costs or service costs, and the need for internal control to keep an eye on how these technologies are being used and how well they work. And to find out the effect of internal control on the implementation of costing techniques in Iraqi companies, 64 questionnaires were given to people who work in the i

The research seeks to highlight the importance of digital finance in banking by providing financial and banking services and its role in improving the access of financial services to customers at the farthest possible point by using modern technology to finance their needs by granting them cash credits through electronic payment tools to facilitate them and shorten time and effort as well as Low cost, and this cannot be achieved without concerted efforts and the provision of basic infrastructure that includes connecting the Internet to all targeted areas, whether cities or rural areas, as well as distributing the largest possible number of ATMs and sending specialized teams to those areas that develop in customers the culture of digital

Polycystic ovary syndrome (PCOS) referring to a syndrome that is recognized as a life-course disease and has both metabolic and reproductive signs; main pathophysiological cause includes insulin resistance, hyperandrogenism, and oxidative stress state. The study aimed to assess the impact of combining Myoinositol and Metformin, the main insulin-sensitizing drugs, on improving clinical, metabolic, and hormonal parameters in females with PCOS. A clinical trial that was prospective, randomized, and comparative on 54 patients (aged 18-40 y) are divided into three groups: group1 patients allocated to receive Myo-inositol(4g), group2 patients assigned to receive Metformin(1g) and group3 patients assigned to receive Myo-inositol(4g) + Metformin