<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver operating characteristic ROC). Dataset was downloaded from UCI ml repository; it is composed of 9 attributes and 699 samples. The findings are clearly showing that the RBF NN classifier is the best in prediction of the type of breast tumors since it had recorded the highest performance in terms of correct classification rate (accuracy), sensitivity, specificity, and AUC (area under Receiver Operating Characteristic ROC) among all other models.</p>
Fifty three hydatid cysts were collected from different hosts, sheep, goats and cattle , from many slaughterhouse in Salahadin and Baghdad , while human's hydatid cysts samples were collected from Tikrit educational hospital and Tofiqe civilian hospital patients . The study included a biochemical comparison of some hydatid cyst fluid criteria such as, glucose, total protein, pH, glutamate pyrovate transaminase enzyme (GPT) , glutamate oxaloacetate transaminase enzyme (GOT) , acid phosphatase (ACP) , Alkaline Phosphatase (ALP) , and also studied protoscolices viability,the current study showed the differences in chemical composition of hydatid cyst fluids back to host type and parasite strain .
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreRegression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well- Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.
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... Show MoreColorectal cancer (CRC) is the most common disease and cause of death globally. The aim of the study is investigation and detection of some bacterial interfering with CRC occurrence and progression. The study conducted between September 2022 till February 2023, a total of 50 specimens were collected from confirmed CRC patients. In addition, 50 stool specimens were collected from Healthy volunteers, considers as control group. Isolation and identification of bacteria in all collected specimens were done by using cultural and differential media (blood agar, macconkey agar and Pfizer agar), as well as the VITEK- 2 compact system. The bacterial species, in the specimens of control were ( Escherichia coli 50 (86.20%), Klebsiella Pneumoni
... Show MoreBackground: With the increase in composite material use in posterior teeth, the concerns about the polymerization shrinkage has increased with the concerns about the formation of marginal gaps in the oral cavity environment. New generation of adhesives called universal adhesive have been introduced to the market in order to reduce the technique sensitive bonding procedures to give the advantage of using the bonding system in any etching protocol without compromising the bonding strength. The aim of the study was to study marginal adaptation of two universal adhesives (Single bondâ„¢ Universal and Prime and Bond elect) using 3 etching techniques under thermal cycling aging. Materials and Methods: Forty-eight sound maxillary first premola
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