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Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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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%.

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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
Validation of Time-Safety Influence Curve Using Empirical Safety and Injury Data—Poisson Regression
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
CD49d and CD26 in chronic lymphocytic leukemia: their correlation with clinical Binet staging and clinical parameters
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The study aimed to assess the expression of CD49d and CD26 in newly diagnosed CLL patients and find their correlation with clinical Binet stage, and other clinical parameters. This study was conducted on 51 newly diagnosed CLL patients based on lymphocyte count > 5×109/L and immunophenotyping. The expression of CD49d, and CD26 were investigated using eight-color flow cytometer. The expression of CD49d and CD26 were detected in 56.9 %, 68.8 % of CLL patients, respectively. The correlation between CD49d expression and CD26 expression was statistically significant (p < 0.001) with high concordance rate between them. The positive expression of both CD49d and CD26 had statistically significant association with clinical Binet staging (p < 0.001,

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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
Evaluation of Raw and Drinking Water for Diyala Governorate (2017)
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The study examined the assessment of raw water and drinking water projects of  Diyala Governorate for the year 2017, amounting to (24) projects, The average per capita supply of potable water (0.396 m3 / day/person), which is less than the global standard for the average per capita of drinking water, and constitute water rumors within the network of water transport in the province (3%), and the water of raw and drinking value within the limits allowed to be used by Iraq and the global indicators of {Total acidity, alkaline, acidic function, chlorides, magnesium, Electrical conductivity, total soluble salts, sodium, potassium, sulfates, turbidity other than (raw water)}. While the index of calcium only a value higher than the limits

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
Impact of evaluation of investment projects in achieving competitive strategy
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The aim of the research is to determine the impact of evaluation of investment projects after the preparation of investment budgets taking into consideration within the investment budgets the concept of competitive strategy, as the harmony between the preparation of investment budgets and competitive strategy will contribute to the success of economic unity and achieve profits well and achieve a competitive advantage. Strategies for economic units because the most important factor to them is the costs produced and the progress of the research problem is focused on "Is it possible to include a strategy of competition, especially within the investment budget when prepared The study concluded that the investment plan prepared by the

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
The Learning Style for distinguished students and their ordinary mates in the secondary stage in accordance to some variables
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The current problem is summarized in what is called the development failing experience
in comprehencing the studying materials , so the students will feel worry of repeating failure
in he future , so he would seek blind keeping on heart for the studying material bond this isbad due to the forgetting in the future , one side of thesis research problem is that there is
many contradictory researches result in relation to the learning styles which impose the
nessicity to find results lessen this contradiction . the importance of the research is
summarized in the importance of the subject under the study , in that the researcher ( as in
her knowledge ) did not find a thesrs tackling the subject of the distinguished students

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Publication Date
Sat Jun 30 2018
Journal Name
Kufa Journal For Agricultural Sciences
Effect of numbers of blades and speed of tillage in the performance of the rotavator plow
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Experiment Factorial conducted with two factor in field texture silt clay loam soil, the first factor were Two Rotavator plow which different in number of rotary blades on flanges, weight, width, made and type, the second factor were four speeds tractor 2.62, 5.10, 7.55, 9.23 km/hr to compare performance two Rotavator under depth 12 cm and knowledge slippage, distance between beat blades, practical productivity, disturbed soil volume, percentage of the soil clods which have diameter less than 5 cm under complete block design with three replications using Least Significant Design 0.05. Results showed Galucho Rotavator recorder the higher practical productivity 0>7089 ha/hr, disturbed soil volume 809.8 m3/hr, percentage of the soil clods 96.1

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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Current Medical And Applied Science
Evaluation of Postgraduate Clinical Educational Environment in The Context of Iraqi Medical Education.
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Background: A carefully planned clinical medical education is critical for the provision of supportive clinical educational environment. The latter will ensure effective teaching, active learning and good attitudes and performance at the bedside. The aim of this study was to evaluate clinical learning environment at AL-Diwaniyah Teaching Hospital. Materials and Methods: A descripitive cross-sectional study involved resident doctors from Internal Medicine and Surgery departments who had six months or more residency training in the respective departments. Data were collected using the Postgraduate Hospital Educational Environment Measure. Data where analyzed using the Statistical Package for Social Sciences version 21.0 and presented us

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Mon Sep 13 2021
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Cutting Parameters for Milling Process of (4032) Al-Alloy using Taguchi-Based Grey Relational Analysis
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The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w

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