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Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of Deep Bayesian Neural Network (DBNN) for the personalized treatment of leukemia cancer has shown a significant tested accuracy for the model. DBNNs used in this study was able to classify images with accuracy exceeding 98.73%. This study depicts that the DBNN can classify cell cultures only based on unstained light microscope images which allow their further use. Therefore, building a bayesian‐based model to great help during commercial cell culturing, and possibly a first step in the process of creating an automated/semiautomated neural network‐based model for classification of good and bad quality cultures when images of such will be available.

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Strategic Intelligence in Organizational Success Analytical research in the colleges of the University of Fallujah
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The current research aims to verify the role of strategic intelligence as an explanatory variable in organizational success as a respondent variable in the colleges of the University of Fallujah, the research community. (Dean, Associate Dean, Section Head, Division Officer, Unit Officer), The researcher used the questionnaire as the main tool to collect data that included (50) items, in addition to using personal interviews and field observations as aids in data collection. The researcher relied on statistical programs (SPSS V.25; Excel V (16) In the treatment and analysis of data through the use of the most appropriate statistical methods (arithmetic mean, standard deviation, difference coefficient, determinatio

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Publication Date
Wed Aug 01 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Slow sand filtration as a tertiary treatment for the secondary effluent from sewage treatment plant
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A field-pilot scale slow sand filter (SSF) was constructed at Al-Rustamiya Sewage Treatment Plant (STP) in Baghdad city to investigate the removal efficiency in terms of Biochemical Oxygen Demand (BOD5), Chemical oxygen demand (COD), Total Suspended Solids (TSS) and Chloride concentrations for achieving better secondary effluent quality from this treatment plant. The SSF was designed at a 0.2 m/h filtration rate with filter area 1 m2 and total filter depth of 2.3 m. A filter sand media 0.35 mm in size and 1 m depth was supported by 0.2 m layer of gravel of size 5 mm. The secondary effluent from Al-Rustamiya STP was used as the influent to the slow sand filter. The results showed that the removal of BOD5, COD, TSS, and Chloride were

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Publication Date
Sun May 01 2022
Journal Name
Expert Systems With Applications
Novel large scale brain network models for EEG epileptic pattern generations
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Selecting the optimal movement subset with different pattern recognition based EMG control algorithms
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi Journal Of Science
Paper based glucose biosensor depending on SPCE modified with hemoglobin and silver nanoparticles
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The direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li

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Publication Date
Sun Dec 14 2025
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Sat Aug 01 2020
Journal Name
Computational Biology And Chemistry
A graph-based multi-sample test for identifying pathways associated with cancer progression
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Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
Treatment of localized vitiligo with 1% pimecrolimus Cream versus 0.05% clobetasol propionate cream—single, blinded, comparative therapeutic trial
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KE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3

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Publication Date
Sun Sep 02 2012
Journal Name
Baghdad Science Journal
Study the expression level of beta 2 microglobulin gene on hepatitis C patients before and after treatment with interferon
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This study has been carried out to evaluate the expression level of beta 2 microglobulin gene on patients infected by hepatitis C virus before and after treatment with interferon. The study included 117 hepatitis C patients comprising as 63 pre-treated patients, the range of age was between 20-65 year with a mean age of 48.12 ± 16.1 and 54 post-treated patients with age range was between 23-63 year with the mean of 46.1 ± 18.1. Also it was found that more than half of patients were located within third and fourth decade i.e. 30-49 year, with a percentage of 52.4% and 55.6 % for pre-treatment and post-treatment patients respectively. Moreover , regarding both groups, males are more than females with the ratio of ( 3.2:1) among p

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Publication Date
Thu Apr 01 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Evaluation of Nesfatin – 1 and Other Biochemical Markers in diabetic Neuropathy Iraqi patients before and after treatment with tegretol
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Diabetic neuropathy is a form of nerve damage that can occur in people who have diabetes. High blood sugar (glucose) induced nerve damage in every part of the body. The nerves in the legs and feet were the most frequently affected. The extent to which a diabetic patient's body is impaired is calculated by the degree of nervosa harm.The purpose of this present study is estimation BMI,IL-10 , nesfatin-1 and HS-CRP in Iraqi DN patients before and after treatment via tegretol as well as it is the first study sheds light on the relationship between Nesfatin -1 and other parameters ( BMI,IL-10 and HS-CRP) also predication of Nesfatin-1 as a newly biomarker in patients with diabetic neuropathy. The present study consist of from 30 cohort G1 as hea

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