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

The aim of the study is to assess the risk factors which lead to myocardial infarction and relation to some variables. The filed study was carried out from the 1st of April to the end of Sept. 2005. The Sample of the study consisted of (100) patients in lbn-Albeetar and Baghdad Teaching Hospital. The result of the study indicated the following; 45% of patients with age group (41-50) were more exposed to the disease and there is no significant difference was seen in the level of education, Martial status, weight and height. The result shows that there are significant difference in risk factors like hypertension, cholesterol level in blood and diabetes. When analyzed by T.test at level of P < 0.01 and there are significant difference in smoki

Asthma is a chronic disease characterized by inflammatory events in the airways, that makes breathing a hard process in these patients. Angiotensin II (AngII) is important regulator for aldosterone production. Also, it participates in inducing reactive oxygen species (ROS) and inflammatory events. Angiotensin-converting enzyme (ACE) is responsible for the production of AngII. We hypothesised that ACE and AngII participate in the progression of asthma by increasing ROS production and inflammatory processes. Thus, we evaluated the level of AngII, the activity of ACE, and the level of malondialdehyde (MDA) as indicators for oxidative stress in 60 asthmatic male patients and 30 non-asthmatic male control. An asthma control test (ACT) was estima

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

Objective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th