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
Breast cancer is the most prevalent malignancy among women worldwide, in Iraq it ranks the first among the population and the leading cause of cancer related female mortality. This study is designed to investigate the correlations between serum and tissue markers in order to clarify their role in progression or regression breast cancer. Tumor Markers are groups of substances, mainly proteins, produced from cancer cell or from other cells in the body in response to tumor. The study was carried out from April 2018 to April 2019 with total number of 60 breast cancer women. The blood samples were collected from breast cancer women in postoperative and pretherapeutic who attended teaching oncology hospital of the medical city in Baghdad and
... Show MoreRecently Tobit Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique and Bayesian hierarchical model with adaptive ridge regression technique .
in double adaptive elastic net technique we assume different penalization parameters for penalization different regression coefficients in both parameters λ1and λ2 , also in adaptive ridge regression technique we assume different penalization parameters for penalization different regression coefficients i
... Show MoreThis research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being
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In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach
... Show MoreMammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti
The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo
... Show MoreThis paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.
In this research, a mathematical model of tumor treatment by radiotherapy is studied and a new modification for the model is proposed as well as introducing the check for the suggested modification. Also the stability of the modified model is analyzed in the last section.
New chelating ligand derived from triazole and its complexes with metal ions Rhodium, Platinum and Gold were synthesized. Through a copper (I)-catalyzed click reaction, the ligand produced 1,3-dipolar cycloaddition between 2,6-bis((prop-2-yn-1-yloxy) methyl) pyridine and 1-azidododecane. All structures of these new compounds were rigorously characterized in the solid state using spectroscopic techniques like: 1HNMR, 13CNMR, Uv-Vis, FTIR, metal and elemental analyses, magnetic susceptibility and conductivity measurements at room temperature, it was found that the ligand acts as a penta and tetradentate chelate through N3O2, N2O2, and the geometry of the new complex
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