Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculated with risk mortality at 5 and 10 years depending on the number of unknown factors. The new system presented in a graphical user interface to facilitate the friendliness at the user side.
The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability
... Show MoreTwo novel demountable shear connectors for precast steel-concrete composite bridges are presented. The connectors use high-strength steel bolts, which are fastened to the steel beam with the aid of a special locking configuration that prevents slip of bolts within their holes. Moreover, the connectors promote accelerated construction and overcome typical construction tolerances issues of precast structures. Most importantly, the connectors allow bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (3) steel beams can be replaced, while precast
... Show MoreTransdermal drug delivery has made an important contribution to medical practice but has yet to fully achieve its potential as an alternative to oral delivery and hypodermic injections. Transdermal therapeutic systems have been designed to provide controlled continuous delivery of drugs through the skin to the systemic circulation. A transdermal patch is an adhesive patch that has a coating of drug; the patch is placed on the skin to deliver particular amount of drug into the systemic circulation over a period of time. The transdermal drug delivery systems (TDDS) review articles provide information regarding the transdermal drug delivery systems and its evaluation process as a ready reference for the research scientist who is involved
... Show MoreWith the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.
Background: Diabetic nephropathy (DN) is a significant contributor to end-stage renal failure in individuals with type 2 diabetes mellitus (T2DM). Diabetic nephropathy is characterized by tubular atrophy, glomerular dilation, glomerulosclerosis, interstitial fibrosis, and proteinuria, resulting in deterioration of kidney function. DN, primarily caused by hyperglycemia, accounts for millions of deaths globally and is the leading cause of end-stage renal disease. Matrix metalloproteinase 10 is an enzyme essential for the breakdown of extracellular matrix constituents. Fetuin-A forms soluble complexes with calcium and phosphate to prevent soft tissue mineralization Objectives: To determine the levels of Matrix Metalloproteinase 10 and
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