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Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization of critical hyperparameters, such as layer count, neuron count per layer, learning rate, and batch size. Utilizing a diverse dataset comprising DNA sequences fromtwo distinct groups: patients diagnosed with breast cancer and a control group of healthy individuals. The model showcased remarkable performance, with accuracy, precision, recall, F1-score, and area under the curve metrics reaching 0.871, 0.872, 0.871, 0.872, and 0.95, respectively, outperforming previous models. These findings underscore the significant potential of DL techniques in amplifying the accuracy of disease diagnosis and prognosis through DNA sequencing, indicating substantial advancements in personalized medicine and genetic counseling. Collectively, the findings of this investigation suggest that DL presents transformative potential in the landscape of genetic disorder diagnosis and management.

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm
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In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

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Publication Date
Wed Apr 01 2020
Journal Name
Indian Journal Of Public Health
Green and Efficient Composition and Diagnosis of Pentdentate Schiff Base Donative Metal Complexes: Antimicrobial, Antifungal, Antioxidant Screening and DNA Binding
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Background: Enforcement of sustainable and green chemistry protocols has seen colossal surge in recent times, the development of an effective, eco-friendly, simple and novel methodologies towards the synthesis of valuable synthetic scaffolds and drug intermediates. Recent advances in technology have now a more efficient means of heating reactions that made microwave energy. Efforts to synthesize novel heterocyclic molecules of biological importance are in continuation. Microwave irradiation is well known to promote the synthesis of a variety of organic and inorganic compounds. The aim of current study was to conceivea mild base mediated preparation of novel Schiff base of 2-Acetylpheno with trimethoprim drug (H2TPBD) and its complexes w

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Publication Date
Fri Jan 06 2023
Journal Name
Journal Of Advanced Biotechnology And Experimental Therapeutics
Evaluation of oxidative stress activity and the levels of homocysteine, vitamin B12, and DNA methylation among women with breast cancer
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Breast cancer (BC) is the most common malignant tumor in women and the leading cause of cancer deaths worldwide. This work was conducted to estimate the roles of oxidative stress, vitamin B12, homocysteine (HCY), and DNA methylation in BC disease progression. Sixty BC patients (age range 33–80 years) and 30 healthy controls were recruited for this study. Patients with BC were split to group 1 consisted of stage II BC women (low level), and group 2 consisted of patients in stages III and IV (high level). Malondialdehyde (MDA), glutathione peroxidase 3 (GPX3), HCY, and vitamin B12 levels in the study groups were measured. Also, the 5-methylcytosine (5mC) global DNA methylation levels were evaluated. The results showed a significant

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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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
Wed Nov 13 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
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 regi

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Publication Date
Sat Jan 01 2022
Journal Name
Wiadomości Lekarskie
EVALUATION OF SEROLOGICAL SCREENING AND PCR-AMPLIFICATION OF HEPATITIS B VIRUS DNA AMONG IRAQI BLOOD DONORS
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The aim: Infection with the hepatitis B virus (HBV) caused by blood transfusion is a big problem throughout the world. The aim of study is to determine the faster and more accurate methods for detection of hepatitis B infections by serological screening and PCR- amplification. Materials and methods: A total of 140528 donors were tested for HBsAg and total anti-HBc from January to October 2021 in Iraq’s National Blood Transfusion Center; however, only 100 samples with HBsAg (-) and anti-HBc (+) were collected and tested for HBV DNA using quantitative real-time PCR. Results: From 2015 to 2021, the percentage of HBsAg positive donors was 0.33 percent in 2015, 0.32 percent in 2016, 0.30 percent in 2017, 0.28 percent in 2018, 0.23 pe

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