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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
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Comparative Study of Genomic DNA Extraction Protocols from Whole Blood for P53 Gene Polymorphism in Persons with and without Prostate Cancer
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In latest decades, genetic methods have developed into a potent tool in a number of life-attaching applications. In research looking at demographic genetic diversity, QTL detection, marker-assisted selection, and food traceability, DNA-based technologies like PCR are being employed more and more. These approaches call for extraction procedures that provide efficient nucleic acid extraction and the elimination of PCR inhibitors. The first and most important stage in molecular biology is the extraction of DNA from cells. For a molecular scientist, the high quality and integrity of the isolated DNA as well as the extraction method's ease of use and affordability are crucial factors. The present study was designed to establish a simple, fast

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Thu Sep 15 2022
Journal Name
Al-academy
The semiotic approach in analyzing contemporary graphic text
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With a great diversity in the curriculum contemporary monetary and visions, and development that hit the graphic design field, it has become imperative for the workers in the contemporary design research and investigation in accordance with the intellectual treatises and methods of modern criticism, because the work design requires the designer and recipient both know the mechanics of tibographic text analysis in a heavy world of texts and images varied vocabulary and graphics, and designer on before anyone else manages the process of analysis to know what you offer others of shipments visual often of oriented intended from behind, what is meant, in the midst of this world, the curriculum Alsemiae directly overlap with such diverse offer

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of parameters of two-dimensional sinusoidal signal model by employing Deferential Evaluation algorithm and the use of Sequential approach in estimation
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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

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Publication Date
Mon Jan 21 2019
Journal Name
International Journal Of Pharmaceutical Quality Assurance
Genetic Assessment of Antibiotic Resistance in Salmonella Enteric a Serovar Typhi in Kirkuk Province
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Around fifty isolates of Salmonella enterica serovar Typhi were isolated from blood specimens of patients referring to several hospitals in Kirkuk province, Iraq. The results revealed that all isolates developed resistance to trimethoprim-sulfamethoxazole and chloramphenicol. However, neither sul2 nor tem genes were detected. Moreover, only ten isolates were positive for catP. Our data suggested participation of other genes or mechanisms allow these multidrug isolates to resist the antibiotics in question.

Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
The genetic inhibition of some pathogenic bacterial isolates related to Enterobacteriaceae by using Different leaves extracts of Cider (Nabag) Zizyphus spina-christa
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The plant Zizyphus spina-christa grows wildly in the middle and southern of Iraq locally named Nabag. In this study the antibacterial activity of several different plant extract (alcoholic hot and cold extract 80%, aqueous hot and cold extract) was tested against some gram negative bacteria that related to Enterobacteriacea as follow; Pseudomonas aeruginosa, Escherchia coli Proteus mirabilis, Serratia mercesence,. Aeromonas sp, Klebsiella pneumoniae ,Shigella sp, Salmonella enteritidis (134), S. typhi(97), S. typhimurium (300) , S. typhi, . The results showed that efficient method of extract was alcoholic hot extract from other extract methods that are used in this study. The detection of active compound in crude extracts of the leaves show

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Publication Date
Sun Mar 03 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

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