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Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy. Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when appropriate, was used to analyze the relationship between the variables. Results: there was a significant reduction of RI mean, PI mean, and S/D ratio among women with different types of abnormal pregnancy compared with the control group. RI and PI mean levels were significantly lower in women with hydatidiform mole and significantly higher in women with missed miscarriage. Lower left S/D mean level was significantly associated with hydatidiform mole and upper left S/D level was associated significantly with control women. For prediction of missed miscarriage; right and left uterine artery RI shows a sensitivity of 80%, 73.3%, a specificity of 68%, 71.1%, and the highest AUC was 0.78 for both.For prediction of molar pregnancy, right and left uterine artery RI showed a sensitivity of 63% for both, a specificity of 54.4%, 60%, and the highest AUC was 0.58, 0.61 respectively. Conclusions: Uterine artery Doppler ultrasonography at 6-12 weeks of gestation is predictive for early pregnancy complications such as missed abortion, hydatidiform mole, and blighted ovum.

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Rutting Prediction of Asphalt Mixtures Containing Treated and Untreated Recycled Concrete Aggregate
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Rutting is a crucial element of the mechanical performance characteristics of asphalt mixtures, which was the primary target of this study. The task involved substituting various portions of virgin coarse aggregate with recycled concrete aggregate materials that had been treated or left untreated at rates ranging from 25 to 100%, with a constant increase of 25%. The treatment process of recycled concrete aggregate involved soaking in acetic acid, followed by a mechanical process for a short time inside a Los Angeles machine without the balls. This research utilized two primary tests: the standard Marshall test to identify the optimal asphalt contents and the volumetric characteristics of asphalt mixtures. The other one w

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Thu Jan 02 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum parathyroid hormone and total serum calcium levels in mild &amp; severe preeclampsia versus normal pregnancy
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Background: Preeclampsia (PE) is a major cause of maternal morbidity and mortality, complicating 3-14% of all pregnancies. Although the etiology remains unknown, placental hypoperfusion and diffuse endothelial cell injury are considered to be the central pathological process; many endocrinological changes have been linked to the etiology of preeclampsia including parathyroid hormone and calcium level. Objective: to compare serum parathyroid hormone and total serum calcium levels in mild and severe preeclampsia versus normal pregnancy. Patients and methods: Serum parathyroid hormone (PTH) level and total serum calcium level were measured in thirty normotensive pregnant women and thirty women with mild preeclampsia and thi

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Publication Date
Mon Jan 01 2024
Journal Name
Revista Brasileira De Saúde Materno Infantil
Misoprostol and mid trimester termination of pregnancy in patients with two previous scars and more at Elwiya Maternity Teaching Hospital
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Abstract Objectives: to determine efficiency and safety of three misoprostol regimens for 2nd trimester pregnancy termination in individuals with two or more cesarean section scars. Methods: a cross-sectional study included 100 pregnant ladies at 13th-26th weeks gestation with previous two cesarean sections (CSs) who were scheduled for pregnancy termination using misoprostol. Patients were conveniently assigned to 100µg/3h, 200µg/3h or 400 µg/3h regimens. Primary outcome was time to abortion, secondary outcomes were side effect and complications. Results: a significant association was found between number previous CSs and longer time to abortion (p=0.01). A highly significant association was identified between earlier gestatio

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Publication Date
Sun Sep 25 2022
Journal Name
Lubricants
Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

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Publication Date
Fri Dec 01 2017
Journal Name
British Journal Of Oral And Maxillofacial Surgery
A novel approach for the three-dimensional evaluation of facial asymmetry of unilateral cleft lip and palate patients (UCLP)
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