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Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the infection. Smart technologies have provided the medical field with health predictions for early detection, and digital diagnosis is one of the most important sources on which research has relied on. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Comparative study of oxidative stress in diabetes mellitus
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The aim of the study was comparative between oxidative stress in diabetes mellitus using the measurement of some biophysical and biochemical parameters on two groups of diabetic patients, were conducted in the Al-Yarmuk Teaching Hospital,30 patients insulin dependent diabetes mellitus (IDDM) or type 1 ,their ages ranged between (15-45) and30 patients non- insulin dependent diabetes mellitus (NIDDM) or type 2,their ages ranged between (42-65).This study has been compared with 30 healthy subjects. The present study was demonstrated to evaluate the alteration in oxidative stress as measured by plasma and red blood cells Malondialdehyde (MDA) andchanges in antioxidant mechanism as measured by plasma and red blood cells Glutathione (GSH)

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Publication Date
Tue Aug 01 2017
Journal Name
Veterinary World
Therapeutic uses of epicatechin in diabetes and cancer
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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Tue Dec 23 2025
Journal Name
Al–bahith Al–a'alami
THE PREVAILING SCIENTIFIC VALUES IN CHILDREN'S PROGRAMS PROVIDED BY MBC3
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The main problem of this research titled (the prevailing scientific values in children's programs provided by the channel (mbc3) is the disclosure of the scientific values that are included in the children's program in the mbc3 channel) which are directed to an important group of society, which is the category of children who spend long hours in front of TV screens to watch these programs, and therefore they acquire many values that can replace fixed values, such as social, moral, religious, etc., and the content analysis method has been used to analyze children's programs presented by mbc3 channel), and the research has reached a number of The results can be summarized b To come:

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of Engineering Science And Technology
INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Symlet Analysis for ECG-Based Diagnosis of Heart Dysfunction
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Publication Date
Sat Feb 09 2019
Journal Name
Iraqi Journal Of Laser
Primary Diagnosis of Abnormal Urine via Auto Fluorescence Process
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The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser

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Publication Date
Tue Jul 01 2003
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
DIAGNOSIS OF SOME PATHOGENIC FUNGI ON SELECTED LOCAL WOODS
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To explore the durability of some local species of wood to fungal deterioration among the
storage period, this research has conducted on three species Eufcalyptus cammaldulensis,
Juglans regia, presence of some genus of fungi; Aspergillus, Penicillium,Botryoderma,
Chaetomium, Phoma, Cladosporium and Pacilomyces in different intensities.
The two fungi Aspergillus and Penicillium appeared more dominants than others, therefore
they were chosen for the pathogenicity test. The results showed that the two species of fungi
preferred Juglans wood firstly were the size of infection was more than 10 times of any of the
other two woods. Eucalyptus showed similar response to that of Morus, but with Aspergillus
it was few bett

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