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.
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.
This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreThe present study aimed to investigate the anatomy, histology, and immunohistochemistry of parathyroid gland in two Iraqi mammals (Weasel, Herpestes javanicus and Long-ear hedgehog, Hemiechinus auritus) as a comparative study. A total of (20) animal for each species were used in the present study. Animals collected were immediately anesthesia and dissected to get the parathyroid gland. Methods of Humason and Bancroft and Stevens were employed for histological techniques. Different stains were used (Hematoxylin- Eosin stain-(H & E), Periodic Acid Schiff stain-(PAS), Azan stain, and Methyl Blue stain-(MB)) for staining the histological sections. Anti-calcitonin, code140778 marker used for immune-histochemical study. Results of the present stu
... Show MoreThis research aims to study the mechanism of application of international specification requirements (ISO 9001: 2015) at the Iraqi Center- Korean Vocational Training return to vocational training department at the Ministry of Labour and Social Affairs for the purpose of preparing and creating the center to get a certificate of conformity with the requirements of the standard (ISO 9001: 2015) that would elevate the level of performance and services provided in the respondent Center after it is identified and the study of the reality of the quality management system by identifying strengths and weaknesses in the system to diagnose the gap and find ways to address that gap, and adopted the researchers the case study method to conduc
... Show MoreBackground: Type 2 diabetes mellitusand chronic periodontitis hold a close relationship that has been the focus of many researches. Currently there is an appreciation to the role of adipose tissue-derived substances "the adipokines" in immune-inflammatory responses; also, there is an interest in using the simple non-invasive saliva in diagnosing and linking oral and general health problems. The current study aims to determine the periodontal health status in the chronic periodontitis patients with and without poorly or well controlled type 2 diabetes mellitus, measure the salivary levels of two adipokines "leptin and resistin", pH and flow rate and then correlate between these clinical periodontal, biochemical and physical parameters in eac
... Show MoreYohimbine is actually confirmed in the United States to be utilized for erectile dysfunction; and recently such drug has become commonly used in body-building communities for its presumed lipolytic and sympathomimetic effects. But ingestion of such drug can bring about epileptic neurotoxic effects.
Many antiepileptic drugs can be utilized to counteract myoclonic seizure; furthermore, diazepam can be used to oppose such type of seizure; in addition, surrogate therapeutic options such as omega 3 may also be utilized.
In this study, twenty-four (24) mice of both sexes weighing 20-25g were randomly-allocated into 4 groups (6 animals each group) as follows: Group I-
... Show MoreObjective: To compare distal tibia nonunion plating and grafting with and without platelet-rich plasma (PRP) regarding union rate, union time and complications Conclusion: Combining PRP with autologous bone graft results in a higher union rate, less healing duration, less post-operative pain, and more callus formation. (Rawal Med J 202;45:629- 632). Methodology: In this prospective comparative study, 32 patients with nonunion tibia from July 2017 January 2019 were divided into two groups: group A (16 cases) were treated by plating and grafting with PRP and group B (16 cases) were treated by plating and grafting only. Keywords: Tibial nonunion, bone graft, plateletrich plasma. Results: There was higher union rate in group A related to group
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