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.
In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources. Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreGestational diabetes mellitus (GDM) is a growing health concern that usually appears during the second and third trimester stage of pregnancy and is characterized by carbohydrate intolerance of variable severity. The aim of the present study was to scrutinize the relationship between the G972R polymorphism of the insulin receptor substrate-1 (IRS-1) gene with GDM in the Iraqi female population. One hundred and twenty of blood samples taken from healthy women (control) and women with gestational diabetes mellitus in 3rd trimester stage of pregnancy, fasting blood glucose (FBG) and HbA1c% measured to diagnose GDM, lipid profile (cholesterol, triglyceride, HDL, LDL, and VLDL), insulin concentration, insulin resistance and beta cell function to
... Show MoreIn this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg
... Show MoreThe role of transmembrane protease serine 2(TMPRSS2) in prostate carcinogenesis relies on overexpression of ETS transcription factors. The aim of this article was to investigate the association of TMPRSS2 polymorphism (rs12329760 (C\T)) with prostate cancer (PCa) in sample of Iraqi patients. One hundred and two individuals were involved in this study for the period from February – 2019 to February – 2020. The sample type was formalin fixed paraffin embedded tissue samples (FFPE), which involved fifty-six samples of pre-diagnosed patients with prostate cancer, aged between 48 and 86 years, and forty-six samples were found to be controls (healthy group) dependent on Prostate Gland integrity, which is the same age as in a group o
... Show MoreIntended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted
... Show MoreThe study was conducted at the fields of the Department of Horticulture and Landscape Gardening, College of Agriculture, University of Baghdad " Abu Ghraib" during the growing seasons 2013-2014 to Evaluate the Vegetative growth , yield traits and genetic parameter of some tomato mutants. Results showed significantly increased of plant height in M6-2 mutant 245cm in Comparison with M6- 3 130 cm . M6-4 mutant significantly increasing of floral clusters 13 . Mutant M6-3 showed significantly increasing the average of, fruit weight 125.9g and plant yield 7.17 kg.plant-1 as comparison with M6-2 which showed decreasing of average of fruit weight and plant yield 79.40g and 4.38 kg.plant-1 respectively. Also results showed the highest Genetic variat
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