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Robust EEG Based Biomarkers to Detect Alzheimer’s Disease
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Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reduction in EEG complexity and decrease in EEG connectivity were investigated. Support vector machine and linear discriminate analysis methods were used to find the best combination of the EEG biomarkers to detect AD with significant performance. A total of 325,567 EEG biomarkers were investigated, and a panel of six biomarkers was identified and used to create a diagnostic model with high performance (≥85% for sensitivity and 100% for specificity).

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Publication Date
Fri Mar 06 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Building HEC-RAS model to detect the areas of Water Cycle Interruption in river stream and their sections
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The purpose of this paper is to build a simulation model by using HEC-RAS software to simulate the reality of water movement in the main river of Basra City (South of Iraq) which is known as Siraji-Khoura River. The main objective of the simulation is to detect areas where the water cycle is interrupted in some stations of the river stream, as this river has become an outlet for the disposal of sewage, leading to pollution and causing weakness in some sections of the river & obstructing the water cycle that takes place between this river and Shatt al – Arab river. A field survey data of the river and its banks were adopted to derive the grades, longitudinal and cross sections of the river, these data included three-dimensional coordinates

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Comparative study on Various Tube Voltages and Contrast Media Doses in CT Pulmonary Angiography to detect Pulmonary Thromboembolism
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Background: Lowering the amount of iodinated contrast material and tube voltage may increase pulmonary artery opacification and thrombus identification without compromising picture quality.

Objectives: To explore the efficiency of using lower tube voltage and a lower contrast medium dose for conducting computed tomography for pulmonary angiography (CTPA) aiming to increase its accuracy in detecting pulmonary thromboembolism (PTE).

Subjects and Methods:100 patients scheduled for CTPA with a preoperative diagnosis of PTE were grouped into two: group A, (50 patients) got 1 mL/kg at 120 kV and group B, (50 patients) received 0.5 mL/kg at 80 kV.The tec

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust Optimization with practical application
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The purpose of this paper is applying the robustness in Linear programming(LP) to get rid of uncertainty problem in constraint parameters, and find the robust optimal solution, to maximize the profits of the general productive company of vegetable oils for the year 2019, through the modify on a mathematical model of linear programming when some parameters of the model have uncertain values, and being processed it using robust counterpart of linear programming to get robust results from the random changes that happen in uncertain values ​​of the problem, assuming these values belong to the uncertainty set and selecting the values that cause the worst results and to depend buil

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Publication Date
Mon Apr 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detect The Infected Medical Image Using Logic Gates
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   This paper determined the difference between the first image of the natural and the second infected image by using logic gates. The proposed algorithm was applied in the first time with binary image, the second time in the gray image, and in the third time in the color image. At start of proposed algorithm the process  images by applying convolution to extended images with zero to obtain more vision and features then enhancements images by Edge detection filter (laplacion operator) and smoothing images by using mean filter ,In order to determine the change between the original image and the injury the logic gates applied specially X-OR gates . Applying the technique for tooth decay through this comparison can locate inj

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Publication Date
Wed Dec 30 2015
Journal Name
Al-kindy College Medical Journal
Cystatin (C) and its correlation to ischemic heart disease
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Background: Cystatin C is recently considered to be a good predictor of cardiovascular morbidity and mortality in patients with coronary artery disease (CAD)Objectives: Correlation between cystatin and ischemic heart disease.Methods :One hundred forty patients (140) with ischemic heart disease admitted to thin study at Baghdad teaching hospital from the period June. 2011 to Jan. 2012. Those patients was categorized into three groups.Group (A): patients with ischemic heart failure.Group (B): Patients with myocardial infarction.Group (C) patients with unstable angina.All these groups were in comparison to fifty (50) healthy controls. Fasting serum citation (C) were measured in all patients and control in addition to all other routine inves

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Robust Estimation For Location Parameter
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 In this paper, we introduce three robust fuzzy estimators of a location parameter based on Buckley’s approach, in the presence of outliers. These estimates were compared using the variance of fuzzy numbers criterion, all these estimates were best of Buckley’s estimate. of these, the fuzzy median was the best in the case of small and medium sample size, and in large sample size, the fuzzy trimmed mean was the best.

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Publication Date
Thu Jul 01 2021
Journal Name
University Of Northampton Pue
Validating a Proposed Data Mining Approach (SLDM) for Motion Wearable Sensors to Detect the Early Signs of Lameness in Sheep
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