Hookah smoking has become very popular in Iraq among women and men. Hookah tobacco contains natural radioactive elements, such as radon, radium, and uranium, as well as toxic elements, such as polonium, which are released during the combustion of tobacco and are inhaled by smoking. Most reviews focus on hookah tobacco, and only a few have investigated the blood of hookah smokers. In this study, a CR-39 detector was used to measure radon, radium, and polonium concentrations and conduct risk assessments in female hookah smokers of different ages. The results show that the concentrations of radon-222, polonium-218, and polonium-214 varied between 61.62 and 384.80, 5.45–33.64 on the wall of the can, and 2.43–15.00 Bq/m3 on the surface of the detector, respectively. The effective radium-226 concentration varied between 4.52 and 56.31 Bq/kg. The absorbed effective dose varied between 1.55 and 9.71 mSv/y, which is within the recommended limit (3–10 mSv/y) by International Commission on Radiological Protection (ICRP). The average case of lung cancer 107.91 cppp, which exceeds the European Union (EU) limit (96.9–104.8 cppp). The rates of radon activity and radon exhalation from the intake of a natural radionuclide due to hookah smoking in a female’s blood were calculated and discussed. This study aimed to establish preliminary results on the risks of radioactivity concentrations and assess the dose in the blood of women who smoke hookah and assess the possibility of developing cancer.
Objectives: To assess the relation between breast cancer & blood groups, identify the importance of women
age group and the relation of age with breast cancer.
Methodology: The study was performed on (115) women who were diagnosed with breast cancer in different
stages of disease and different ages. Blood samples were taken from them to demonstrate their blood groups and
(20) fresh tumor tissue samples were obtained; the tumor tissue used as a source of lectin for hemagglutinate
with erythrocyte of different blood groups. The study conducted at Baghdad Teaching Hospital and Radiation &
Nuclear Medicine Hospital from January, 2007 through June 2007.
Results: The study shows that the highest percentage of women
Lung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr
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To investigate the activity and role of certain enzyme markers in 30 patients female with breast cancer (non-treated, treated, and treatment with recovered).The serum activity of enzyme tumor markers (ALP, GPT and GOT) of (30) patients with breast cancer, and (7) healthy control subjects by using statistical analysis: There is significant difference higher in activity of serum enzyme tumor markers (ALP, GPT, and GOT) in all patients as compared with healthy control
In this study, the activity concentrations of indoor radon, thoron
and their progeny have been measured in air for 61 different
locations of Al-Maddan city using twin cup dosimeter. Furthermore,
some useful parameters concerning the health hazards have been
estimated; working level month (WLM), annual effective dose (Eff),
and excess lung cancer per million person per year (ELC).The results
show that the values of radon gas levels in the investigated districts
varied from 56.28 to 194.43Bq/m3with an overall average value
132.96Bq/m3, while 0.313 to 1.085 for WLM with an overall average
0.740, respectively. The value of Eff and ELC have been found to
vary from 1.420 to 4.918 mSv/y with an overall average valu
Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreThe study involved 120 women, who were distributed into two groups of breast tumor patients (30 malignant and 30 benign) and a group of controls (60 women). The patients were referred to the Center for Early Detection of Breast Tumor at Al-Alwayia Hospital for Gynecology and Obstetrics (Baghdad) during the period June-December 2011. They were investigated for the frequency of ABO blood group phenotypes, menopausal status, oral contraceptive use, body mass index and family history of breast cancer or other cancers. The results demonstrated that 60.0% of malignant cases clustered after the age 50 years, while it was 20.0% in benign cases. Fifty percent of malignant breast tumor patients reached menopause, while in benign cases, the corresp
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