Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning algorithms implementation in the recurrent stroke prediction models. This research aims to investigate and compare the performance of machine learning algorithms using recurrent stroke clinical public datasets. In this study, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Bayesian Rule List (BRL) are used and compared their performance in the domain of recurrent stroke prediction model. The result of the empirical experiments shows that ANN scores the highest accuracy at 80.00%, follows by BRL with 75.91% and SVM with 60.45%.
Background: Treatment of invasive prolactinoma, which has several characteristics including invasive growth into cavernous sinuses and formation of giant adenomas compressing adjacent neural structures, resulting in neurological dysfunction, has been very challenging. There are relatively few reports available describing long-term treatment outcome.
Aims of the study: In this study we evaluate the results of cabergoline administration as initial treatment during 4 years follow up period.
Methods: We prospectively categorized 36 patients into four groups according to the results of 3 months of cabergoline treatment: group 1, tumor volume reduction (TVR) ˃25% with normaliz
... Show MoreBackground: Blastocystis spp. distributes world widely and the genus Blastocystis include many subtypes that are isolated from human intestinal tract. It is considered the most common parasite detected in human being.
Objectives: To evaluate the incidence of Blastocystis spp. among leukemic children, to find out its association with the presence of symptoms (diarrhea and abdominal pain), and to assess the efficacy of different staining methods in detection of Blastocystis spp.
Type of the study: cross-sectional study.
Method: 103 children were enrolled in this study, 53 leukemic patients and 50 healthy con
... Show MoreANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreThe research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests
... Show MoreThe research aimed at identifying the effect of the think, pair, and share strategy by using educational movies on learning jumping opened legs and closed legs skills on vault in artistic gymnastics for women. It also aimed at identifying the group that learned better the skills understudy. The researcher used the experimental method on second-grade College of Physical Education and Sport Sciences female students. Twelve female students were selected from each of the two sections to form the subjects of the study. The main program was applied for eight weeks with one learning session per week. The data was collected and treated using SPSS to conclude that the think, pair, and share strategy and the traditional program have positive effects
... Show MoreMicroalgae have been used widely in bioremediation processes to degrade or adsorb toxic dyes. Here, we evaluated the decolorization efficiency of Chlorella vulgaris and Nostoc paludosum against two toxic dyes, crystal violet (CV) and malachite green (MG). Furthermore, the effect of CV and MG dyes on the metabolic profiling of the studied algae has been investigated. The data showed that C. vulgaris was most efficient in decolorization of CV and MG: the highest percentage of decolorization was 93.55% in case of MG, while CV decolorization percentage was 62.98%. N. paludosum decolorized MG dye by 77.6%, and the decolorization percentage of CV was 35.1%. Metabolic profiling of
... Show MoreThe aim of this study was to Identifying The Effect of using Linear programming and Branching programming by computer in Learning and Retention of movement concatenation(Linkwork) in parallel bars in Artistic Gymnastics. The searchers have used the experimental method. The search subject of this article has been taken (30) male - students in the second class from the College of Physical Education/University of Baghdad divided into three groups; the first group applied linear programming by computer, and the second group has been applicated branching programming by computer, while precision group used traditional method in the college. The researchers concluded the results by using the statistical bag for social sciences (spss) such as both
... Show MoreRecently, environmental noise has arisen from various sources, such as those from exhaust mufflers of combustion engines found in cars, trucks, or power generators, which produce significant noise during their operation. Controlling the radiated noise from these mufflers is a major factor in improving acoustic comfort and minimizing the impact on the surrounding communities. Numerous research has been presented for this reason by modification of the internal structure of the exhaust muffler. The main objective of this work is to reduce the noise level emitted from exhaust mufflers. This can be achieved by adjusting structure parameters to attenuate the surrounding environment's radiated noise. Analysis of pressure-wave propagation h
... Show MoreThe research aims to determine the principles of total quality management (commitment of senior management, product planning, customer satisfaction, process improvement) and its role in promoting employee loyalty through a sample survey of the opinions of managers in public redemption Company. Which amounted to (45) individuals adoption of the questionnaire as a tool head in collecting data and information and their responses were analyzed using several statistical methods, which included (arithmetic mean, standard deviation, correlation coefficient, and the coefficient of simple regression) depending on the program (spss). The research found a group of the most important conclusions from the presence
... Show MoreWith the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev
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