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Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Hypomagnesemia in Iraqi Diabetic Patients and Healthy Controls: An Exploratory study
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Background: Diabetes mellitus has been suggested
to be the most common metabolic disorder
associated with magnesium deficiency, and because
available data suggest that adverse outcomes are
associated with hypomagnesemia, it is prudent that
routine surveillance for hypomagnesemia be done
and the condition be treated whenever possible.
Aim of the study:To explore the serum Mg
concentrations of diabetic patients and healthy
controls in our locality.
Mehtods: One hundred and forty four diabetic
patients (22 with type I and 122 with type II diabetes
mellitus) recruited from the outpatient diabetes clinic
at the Specialized Center For Endocrine DiseasesBaghdad (62 patients), National Diabetes Center-Al

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Publication Date
Sun Aug 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Metabolic Syndrome
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Metabolic syndrome (MetS) is a combination of health disorders that mainly result from overweight and obesity. It increases the risk of developing cardiovascular disease and diabetes. (MetS) closely related to the existence weight gain or Obesity and laziness. It increases the serum levels of TNF-α and change the levels of a number of other parameters (e.g., adiponectin, resistin, and PAI-1). TNF-α dose not only appear to cause the production of inflammatory cytokines. It can trigger cell signaling by interacting with TNF-α receptors that can lead to insulin resistance. Usually, the digestive system molders the foods you eat and converts them to glucose. Insulin is an anabolic hormone produced by the pancreas that aids glucose g

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Publication Date
Thu Sep 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of sweet and salty taste sensitivity on gin-gival health in relation to salivary serotonin among type1 diabetic patients aged 12-14 years
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Background: This study was conducted among diabetic persons to assess the sweet and salty taste sensitivity with its effect on gingival health in relation to salivary serotonin levels. Materials and methods: A cross-sectional comparative study design was used. All patients with diabetes aged 12-14 years that attend the Paediatric hospital at Baghdad medical city with specific inclusion criteria were involved in the sample of the present study (patients group 50 patients) compared with non-diabetic persons matched in age and gender of the study sample (control group 70 patients) who were attending dental unit in the college of dentistry/university of Baghdad. A two-alternative forced choice question including each component presented at f

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Publication Date
Fri Jun 30 2006
Journal Name
Al-kindy College Medical Journal
Oral Carriage Rate of Candida Species in Diabetic Patients
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Background: It is well known that oral carriage
of Candida species increase in many situations, like
obesity, debility, leukemia, viral infection, use of
certain drugs in addition to diabetes mellitus.
Objective: find the relation between diabetes and
its control on oral carriage of Candida.
Methods: Thirty four hundred oral swabs from
diabetic patients 67% are females and 33% are
males, 41.7% are type 1 diabetes and 58.3% are type
2.different culture media are used.
Results: we found that 37.9% of diabetics had oral
carriage, older age group had more but the
difference is not significant statistically P>0.05, in
addition females carry more Candida than males
P<0.05, while type of diabetes

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Publication Date
Sun Apr 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Preparation of One of Metformin Derivatives and Study Its Effect on Some Biochemical Parameters in Blood Sera of Rabbits
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   This study aimed to synthesize a novel amide prodrug of metformin with aspirin by amide bond. The structure was characterized by (FTIR, 1H-NMR, 13C-NMR and CHNO) ,Purification of the prepared compound was using column chromatography.          Using of 40 rabbit having the same weight and devided into 4 groups (4x10) the first group (G1): (the control healthy group) was given drink water and didn’t give any material, second group(G2):( the control infected group) was given hydrogen peroxide concentration  % 0.5 until infecting diabetes  mellitus,  third group(G3): was given hydrogen peroxide concentration as in (G2) and ( 250 mg/kg) of aspirin and (348.8 mg/kg

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
A Visual Interface Design for Evaluating the Quality of Google Map Data for some Engineering Applications
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Today, there are large amounts of geospatial data available on the web such as Google Map (GM), OpenStreetMap (OSM), Flickr service, Wikimapia and others. All of these services called open source geospatial data. Geospatial data from different sources often has variable accuracy due to different data collection methods; therefore data accuracy may not meet the user requirement in varying organization. This paper aims to develop a tool to assess the quality of GM data by comparing it with formal data such as spatial data from Mayoralty of Baghdad (MB). This tool developed by Visual Basic language, and validated on two different study areas in Baghdad / Iraq (Al-Karada and Al- Kadhumiyah). The positional accuracy was asses

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Computer Science And Information Security (ijcsis)
Finite State Automata Generator for DNA Motif Template as Preparation Step for Motif Mining
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There are many tools and S/W systems to generate finite state automata, FSA, due to its importance in modeling and simulation and its wide variety of applications. However, no appropriate tool that can generate finite state automata, FSA, for DNA motif template due to the huge size of the motif template. In addition to the optional paths in the motif structure which are represented by the gap. These reasons lead to the unavailability of the specifications of the automata to be generated. This absence of specifications makes the generating process very difficult. This paper presents a novel algorithm to construct FSAs for DNA motif templates. This research is the first research presents the problem of generating FSAs for DNA motif temp

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Publication Date
Mon Jul 25 2016
Journal Name
Earthquakes And Structures
Vibration response of saturated sand - foundation system
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In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load applied on a footing resting on sandy soil at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into consideration include loading frequency, size of footing and different soil conditions. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used. The footings were tested by changing all parameters at the surface and at 50 mm depth below model surface. Meanwhile, the investigated paramete

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Publication Date
Sun May 30 2021
Journal Name
Gsc Biological And Pharmaceutical Sciences
Revision of some trematodes (Plagiorchiida: Microphallidae) from different birds in Iraq
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The adult worms of the Microphallidae family are mainly found as intestinal parasites of birds and mammals, while metacercariae is most commonly found in decapodal crustaceans. The Microphallidaeare family is spread throughout the world. It includes approximately 47 genera. Mature worms usually enter the digestive system of vertebrates, especially birds and mammals. Microphallidae contain eight subfamilies: Androcotylinae - Basantisiinae - Endocotylinae - Gynaecotylinae - Levinseniellinae - MaritrematinaeMicrophallinae - Sphairiotrematinae. Therefore, due to the lack of studies on the Microphallidae family in Iraq, we began to develop a database on this important family.

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Publication Date
Thu Aug 31 2023
Journal Name
Iraqi Geological Journal
Mineral Inversion Approach to Improve Ahdeb Oil Field's Mineral Classification
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Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

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