The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of 88% and an Accuracy of almost 89%. We also came to the conclusion that the Fibroid mass is small and less white than the Fatty mass
The mechanical function of the heart is governed by the contractile properties of the cells, the mechanical stiffness of the muscle and connective tissue, and pressure and volume loading conditions on the organ. Although ventricular pressures and volumes are available for assessing the global pumping performance of the heart, the distribution of stress and strain that characterize regional ventricular function and change in cell biology must be known. The mechanics of the equatorial region of the left, ventricle was modeled by a thick-walled cylinder. The tangential (circumferential) stress, radial stress and longitudinal stress in the wall of the heart have been calculated. There are also significant torsional shear in the wall during b
... Show MoreThe speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t
... Show MoreAbstract
Objectives: The study aims to: (1) Find out the relationship among participants’ age, body mass index (BMI), and Health Belief Model (HBM) related to colorectal examinations among graduate students. (2) Investigate the differences in Health Belief Model constructs between the groups of age, gender, marital status, and education level among graduate students.
Methodology: A descriptive correlational study design which conducted in the College of Fine Arts – University of Baghdad. A convenience sample of 80 graduate students were included in this study. The data were collected by using a self-reported questionnaire which consisted of two parts (I) socio-demographic characteristics (II) Colorectal Cancer Screening Beliefs
The banking sector is currently facing great challenges resulting from intense competition in the financial environment, and this is what makes the supreme audit bodies and the Central Bank audit as the highest supervisory authority on banks in order to achieve profit and not be exposed to loss, and this requires identifying the banking strengths and risks that constitute points Weakness that affects the future performance and the life of the bank, which requires special supervisory care, and from this point of view, the research aims to use the CAMELS model as a control tool in banks, through the use of its six indicators: capital adequacy, asset quality, management quality, profits, liquidity And sensitivity to market risks, th
... Show MoreThe estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To
... Show MoreIn linear regression, an outlier is an observation with large residual. In other words, it is an observation whose dependent-variable value is unusual given its values on the predictor variables. An outlier observation may indicate a data entry error or other problem.
An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. These leverage points can have an effect on the estimate of regression coefficients.
Robust estimation for regression parameters deals with cases that have very high leverage, and cases that are outliers. Robust estimation is essentially a
... Show MoreBackground: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density v
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