Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased or not.
The study aimed to evaluating the inhibitory activity of apigenin extracted from Salvia officinalis leaves on the growth of L20B cancer cell in vitro, and through two incubation periods; 48 and 72 hours. Accordingly, eight concentrations (1.56, 3.13, 6.25, 12.5, 25.0, 50.0, 100.0 and 200.0 micromol) of apigenin and similar concentrations of vitamin C and carbon tetrachloride (CCl4) were tested. The apigenin revealed its significant inhibitory potentials against the growth of L20B cell line, especially at the low concentrations (1.56, 3.13 and 6.25 micromol) and at 72 incubation period in comparison with vitamin C and CCl4.
Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)
Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreBreast carcinoma is one of the greatest popular neoplasms in females. It is a major reason of demise in the world, and it is the first cancer in ranking diagnosed in Iraqi women. This study aimed to determine aminoacyltRAN-synthetase complex interacting multifunctional protein 1 and liver enzymes levels in Iraqi females with stage II breast malignance, and study the effect of chemotherapy (after surgery) on these markers. This study included 50 females patients with stage II breast malignance (before and after surgery and second dose of chemotherapy) attending the Oncology Teaching Hospital in Medical City/ Baghdad, in addition to 20 persons as controller group were chosen without any chronic diseases. Their ages ranged from (30-55) years.
... Show MoreBackground: Bladder cancer (BC) is the most common malignant tumor in the urinary tract and the tenth most common malignancy worldwide. Exosomes are 40–100 nm-diameter nanovesicles that are either released straight from the plasma membrane during budding or merged with the plasma membrane by multivesicular bodies. Objectives: To assess the proportion of serum and urinary Exosome levels in urinary bladder cancer patients, as well as their impact on the disease. Methods: From January 2023 to June 2023, a total of 45 samples of blood and urine were collected from individuals diagnosed with bladder cancer at the Ghazi Hariri Hospital for Specialized Surgery. They included 45 male and female patients, varying in age, as well as 45 heal
... Show MoreVariable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.