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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
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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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
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Study of the genetic diversity in three species belonging to family: Daphniidae (Crustaceae, Cladocera) collected from different regions in Baghdad Province/Iraq
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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Genetic Polymorphism in TNF-α Promoter Region: Its Association with Severity and Susceptibility to Rheumatoid Arthritis in Iraqi Patients with Active Disease
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Objectives: To study the prevalence of rs1799964 (-1031 T/C) and rs361525 (- 238 G/A) SNPs and their effect on the disease activity, severity, and cytokines production in newly diagnosed Iraqi rheumatoid arthritis patients. Patients and Methods: sixty-three patients were diagnosed by a specialist physician while attending the rheumatology unit and twenty control participated. The inflammatory markers were measured and PCR amplification and sequencing were performed to demonstrate TNF-α SNPs. Results: Regarding (-1031 C/T) SNP, the TT genotype and allele C were significantly present in the controls, and the CT genotype was distributed significantly in the patients. The TT genotype was mostly distributed in the mild-moder

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Publication Date
Wed Jul 30 2025
Journal Name
Iraqi Journal Of Science
Synthesis, Spectral Characterization, DNA Cleavage, and Antioxidant Properties of Metal Complexes with a Novel Schiff Base Ligand Derived from 4-Chlorobenzoic Acid
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A novel Schiff base ligand (DBC) synthesized from 4-chlorobenzoic acid, along with its Cu (II) and Co (II) complexes, was prepared and characterized using FT-IR, 1H and 13C-NMR, UV-Vis spectroscopy, as well as magnetic and conductivity measurements. Based on this, a tetrahedral structure of [M(DBC)Cl2] was proposed for the complexes. Antioxidant activity of the compounds was assessed and compared to ascorbic acid, revealing that the copper complex exhibited superior antioxidant properties compared to the cobalt complex and the ligand. Furthermore, the antibiofilm potential of the copper and cobalt complexes was assessed against five clinically relevant bacterial species (P.aeruginosa, E.coli, K.pneumoniae, S.aureus and S.typhi) usin

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Oxygen Mass Transfer Coefficients in Stirred Bioreactor with Rushton Turbine Impeller for Simulated (Non-Microbial) Medias
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 Abstract

The study of oxygen mass transfer was conducted in a laboratory scale 5 liter stirred bioreactor equipped with one Rushton turbine impeller. The effects of superficial gas velocity, impeller speed, power input and liquid viscosity on the oxygen mass transfer were considered. Air/ water and air/CMC systems were used as a liquid media for this study. The concentration of CMC was ranging from 0.5 to 3 w/v. The experimental results show that volumetric oxygen mass transfer coefficient increases with the increase in the superficial gas velocity and impeller speed and decreases with increasing liquid viscosity. The experimental results of kla were correlated with a mathematical correlation des

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Publication Date
Sun Sep 01 2024
Journal Name
Journal Of Radiation Research And Applied Sciences
Bioaccumulation and translocation of radionuclides heavy metals in Cynodon dactylon: A phytoremediation approach in Al-Dora refinery
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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhancing Spatial Accuracy of OpenStreetMap Data: A Geometric Approach
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OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Efficient Approach for Solving (2+1) D- Differential Equations
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     In this article, a new efficient approach is presented to solve a type of partial differential equations, such (2+1)-dimensional differential equations non-linear, and nonhomogeneous. The procedure of the new approach is suggested to solve important types of differential equations and get accurate analytic solutions i.e., exact solutions. The effectiveness of the suggested approach based on its properties compared with other approaches has been used to solve this type of differential equations such as the Adomain decomposition method, homotopy perturbation method, homotopy analysis method, and variation iteration method. The advantage of the present method has been illustrated by some examples.

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