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A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift algorithm is used for segmenting the affected areas of skin cancer images. Finally, these segmented images are given to a deep learning classifier called Deep forest for prediction of skin cancer. The experiments are carried out on two publicly available datasets called ISIC-2019 and HAM10000 datasets for the analysis of segmentation and classification. From the outcomes, it is clearly verified that the projected model achieved better performance than the existing deep learning techniques.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Evaluating the levels of Tumor Necrosis Factorα-, Interleukin-6 and Vascular endothelial growth factor in patients with Colorectal Cancer
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     Cytokines are polypeptides with several functions that are produced by a variety of bodily cells. They are clinically significant for illness diagnosis, treatment, and prevention. Interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) are the most important cytokines for cell division and proliferation. Vascular endothelial growth factor (VEGF) is produced in excess in mesenchymal, epithelial, and especially in tumor cells. In this study the serum levels of IL-6, TNF-α and VEGF were detected for 41 colorectal cancer patients and 41 healthy control group at Nanakaly Hospital by comparing their serum concentrations for patients paining from colorectal carcinoma (CRC) with those of the control subjects. The result shows a s

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Development Binary Search Algorithm
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There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case com

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Genetic Algorithm Based PID Controller Design for a Precise Tracking of Two-Axis Piezoelectric Micropositioning Stage
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 In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Thu Nov 01 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Factors That Contribute to Bladder Cancer
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Abstract Objective: The study aimed to assess the factors contributes of patient with bladder cancer and to find out the relationship between the factors of bladder cancer with certain variable. Methodology: A descriptive study to assessment of factors that contribute to bladder cancer that was carried out Al-Karama teaching hospital, Al-Kendy teaching hospital, Specialty Surgery teaching hospital and Al-Yarmok teaching hospital for the period of November 2003 to August 2004. A purposive (non-probability) sample of (100) patients with bladder cancer. An assessment from was constructed for the purpose of the st

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Immunohistochemical expression of HepPar 1 in colorectal cancer
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Background: Colorectal carcinoma is common in Northwest Europe, North America, and other Anglo-Saxon areas, while it decreases in number in Africa, Asia, and some parts of South America, There are many immunohistochemical markers react to colonic tissue, the large majority of colorectal carcinomas are positive for mucin stains. Colorectal adenocarcinomas are invariably positive for cytokeratin (CK), Reactivity for CEA is also the rule; as a matter of fact, failure to detect CEA in an adenocarcinoma of makes a colo-rectal site of origin seems to be unlikely, and many other markers that could claimed in colorectal tumors, a one marker that may has a role in staining colorectal tumors is HepPar-1 which is a monoclonal antibody that reacts t

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Medicinal And Chemical Sciences
The Role of Monoamine Oxidase and Atherogenic Index in Newly Diagnosed and Tamoxifen Treated Women with Breast Cancer Disease
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Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were

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Publication Date
Wed Dec 23 2020
Journal Name
2020 International Conference On Advanced Science And Engineering (icoase)
A Comparative Study Using LZW with Wavelet or DCT for Compressing Color Images
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As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
Studying the Chaotic Dynamics Using Rossler-Chua Systems Combined with A Semiconductor Laser
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     In this paper, two different chaotic dynamic systems are coupled using a semiconductor laser to produce a new chaotic system. These two chaotic systems are Rossler and Chua systems. X-dynamic of Rossler system was coupled optically using optical fiber as a carrier of signal with x, y, and z-dynamics of Chua system. The results were analyzed and the behavior of Chua system was found to be changing in time series which, in turn, changed the attractor. The Chua attractor was converted from double scroll to single scroll. The results obtained from connecting two different systems in chaotic behavior showed a remarkable increase in the bandwidth of Chua system. This increase in bandwidth opens up a wide field for many

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