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 study of several classification algorithms by testing 12 different classifiers using two international datasets to provide an accurate indicator of their efficiency and the future possibility of combining efficient algorithms to achieve better results. Finally, building several CBC datasets for the first time in Iraq helps to detect blood diseases from different hospitals. The outcome of the analysis step is used to help researchers to select the best system structure according to the characteristics of each dataset for more organized and thorough results. Also, according to the test results, four algorithms achieved the best accuracy (Logitboost, Random Forest, XGBoost, Multilayer Perceptron). Then use the Logitboost algorithm that achieved the best accuracy to classify these new datasets. In addition, as future directions, this paper helps to investigate the possibility of combining the algorithms to utilize benefits and overcome their disadvantages.
Many people believe that diabetes appears after a psychological crisis, which is a misconception but it could be in them before having a crisis ore the crisis. But emotion increases the appearance of symptoms, and athletes are at risk of developing diabetes. Hypoglycemia is not unusual for athletes, and during physical activity the sugar level changes in the blood. Therefore, it is important to conduct tests for the measurement of sugar before and immediately after the activity, for the purpose of detecting the sharp drop in the sugar level and treating it, and the early detection is necessary to avoid the possibility of diabetes, the concept of psychological immunity in psychology is considered a positive concepts that maintain the balance
... Show MoreThis research deals with the frameworks and mechanisms of international press coverage of the issue of foreign interference in the formation of the Iraqi government in the Saudi newspapers Asharq Al-Awsat and Kayhan Al-Arabi Iran and how this topic was addressed in the two newspapers. The frameworks for international press coverage of external interference in the formation of the Iraqi government. ”This research is one of the descriptive research that adopted the survey method، which made it possible to use the content analysis tool to analyze
the content of the two newspapers، whose numbers are (624) from the
newspapers (Al-Sharq Al-Awsat Al-Saudi Arabia and Kayhan Al-Arabi Iran) from (1/1/2018 to 31/12/2018)، and the researc
Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition
... Show MoreGenetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem
... Show More<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor
... Show MoreToday with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned
The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv
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