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Prediction of maternal diabetes and adverse neonatal outcome in normotensive pregnancy using serum uric acid
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Diabetes mellitus, with adverse neonatal events are challenging issues to all obstetricians and pediatricians, where uric acid could play a vital role. We aimed to assess the relationship and prognostic benefits of serum uric acid measured at about 20 weeks’ gestation in normotensive pregnancy, with subsequent maternal diabetes, and neonatal complications. All singleton normotensive pregnant women with normal blood glucose, serum creatinine, and weight before pregnancy, whom attended Medical City Hospital, Department of Obstetrics and Gynecology in Baghdad, were involved and regarded as the case group, on the condition that their serum uric acid measured at 20 weeks’ gestation > 3 mg/dl, but if ≤ 3 mg/dl, they would be registered as a control group. A complete follow up was performed regularly during pregnancy, and after delivery; regular assessments of maternal blood glucose were done up to one year. Maternal diabetes mellitus (DM), small for gestational age (SGA) neonates, and preterm delivery (PD) constituted (27.59%), (43.60%), and (1.97%), respectively in case group which had significantly included maternal DM and SGA (P <0.001). Also, elevated mid-pregnancy serum uric acid was strongly associated (P <0.0001) with maternal DM (5.86 ± 0.69) and SGA (4.78 ± 0.34). Cut-off values of uric acid of 4.76 mg/dl were best associated with maternal DM, while 4.33 mg/dl with SGA. In conclusion, the cut-off points of 4.76 and 4.33 mg/dl of maternal mid- normotensive pregnancy serum uric acid have the potential ability to predict Maternal DM and SGA, respectively.

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Publication Date
Sat Jan 31 2009
Journal Name
Not Published
Assessment of the pediatric nurse's knowledge about the nosocomial infection in neonatal intensive care unit of Baghdad pediatric teaching hospitals
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Publication Date
Mon Mar 07 2022
Journal Name
International Journal Of Environmental Research And Public Health
Efficacy of MMP-8 Level in Gingival Crevicular Fluid to Predict the Outcome of Nonsurgical Periodontal Treatment: A Systematic Review
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Purpose: To explore whether baseline matrix metalloproteinase (MMP)-8 level in gingival crevicular fluid (GCF) (exposure) can predict the outcome (reduction in probing pocket depth (PPD) (outcome)) of nonsurgical periodontal therapy (NSPT) (manual or ultrasonic or both) in patients with periodontitis (population/problem) after 3 months. Methods: Six databases (PubMed, Cochrane library, ProQuest, Ovid, Scopus, EBSCO) were searched for relevant articles published until 30 July 2021. Retrieved articles were passed through a three-phase filtration process on the basis of the eligibility criteria. The primary outcome was the change in PPD after 3 months. Quality of the selected articles was assessed using Cochrane Risk of Bias tool (RoB2

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Publication Date
Mon Jul 06 2026
Journal Name
Iraqi Journal For Computer Science And Mathematics
Enhanced Intrusion Detection Using Recurrent Neural Networks with Amino Acid Codon Features
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Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

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Publication Date
Fri Jul 19 2024
Journal Name
Baghdad Science Journal
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

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Publication Date
Wed Apr 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Evaluation of some inflammatory cytokines and glycated hemoglobin in uncontrolled type 2 diabetes mellitus with nephropathy
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Background: Chronic hyperglycemia causes diabetic nephropathy(DN), which is a typical microvascular complication of type 2 diabetes mellitus. The pathogenesis of DN is not fully understanding. The inflammation may possess a significant role in the progression of DN in diabetic patients. Method: The study accomplished at teaching laboratories of medical city, Baghdad, Iraq. It was included 50uncontrolled diabetic type 2 patients with nephropathy, age range (40-78) years and 42 controlled diabetics type 2 without nephropathy, age range (35 - 52) years as a control group. The participants divided in to two groups according to HbA1c measurement which is described as follows: < 7.5% of HbA1c describes controlled diabetes, and > 9% of HbA1c

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Publication Date
Sun Oct 21 2018
Journal Name
Al-kindy College Medical Journal
Biochemical Risk Determinants of Osteoporosis in Overweight and Obese Postmenopausal Women with Type 2 Diabetes Mellitus
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Background: Several studies suggested that skeletal system is adversely affected by diabetes and is associated with increased risk of osteoporosis and fragility fractures  

Objectives: The study was a case-control study that designed to assess the level of bone turnover markers (BTMs) among patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of body weight and diabetic control on the level of bone turnover

Type of the study: Cross- sectional study.

Methods: The present study included 100 postmenopausal women with type 2 diabetes mellitus. Sixty-six non-diabetic postmenopausal women were enrolled as a control. Fasting b

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Publication Date
Mon Apr 01 2024
Journal Name
Journal Of Advanced Pharmaceutical Technology &amp; Research
Effects of subclinical hypothyroidism in type II diabetes mellitus patients on biochemical, coagulation, and fibrinolysis status
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The aim of the currnet study to examine the effect of subclinical hypothyroidism (SCH) in diabetic patients on coagulation parameters. This retrospective case–control study involves 130 patients diagnosed with type 2 diabetes mellitus (T2DM), divided into 65 T2DM with newly diagnosed SCH and 65 euthyroid (EUT) T2DM patients without SCH. Fibrinogen (FIB) was significantly higher in SCH (508.2 ± 63.0 mg/dL) than EUT (428.1 ± 44.8 mg/dL). In the SCH patients, FIB correlated with several parameters, such as age (β = 0.396), body mass index (β = 0.578), glycated hemoglobin (β = 0.281), and activated partial thromboplastin time (β = 0.276). In conclusion SCH in DM patients appears to increase the magnitude of coagulopathy.

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Publication Date
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction of Un-Cored Intervals Using FZI Method and Matrix Density Grouping Method: A Case Study of Abughirab Field/Asmari FM., Iraq
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Knowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea

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Publication Date
Thu May 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Channel Estimation and Prediction Based Adaptive Wireless Communication Systems
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Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

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Publication Date
Fri Nov 01 2013
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
Treatment of chronic paronychia: A double blind comparative clinical trial using singly vaseline, nystatin and fucidic acid ointment
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KE Sharquie, AA Noaimi, SA Galib, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 4

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