Background: The early detection of oral cancers gives the greatest chance of curing and the delay in presentation has a significant impact on the associated morbidity and mortality. The lack of general dental practitioners (GDP) knowledge in early cancer detection has been shown to contribute to delays in referral and treatment. The aim of this study was to investigate the oral cancer awareness among a group of GDP by assessing their knowledge of detection and prevention of oral cancer. Materials and methods: A questionnaire based study was designed. The questionnaire was delivered to 200 GDP assessing oral examination method, knowledge of oral cancer risk factors, clinical appearance and the most common site, point of referral and requests for further information. Results: A response rate of 69% was obtained. The GDP were less likely to examine the oral mucosa than other similar studies in other countries, and also less likely to advice patient about risk factors. Smoking and alcohol use wereidentified as risk factors by 96.3% and 43.48% of the GDP respectively. Only 37.7% of GDP believed they had sufficient knowledge of oral cancer, and more than 94% believed they need further information about oral cancer. Conclusion: This study highlights need for more education of the GDP on oral cancer.
Objectives: The specific objectives of the present study were to assess the level of job satisfaction among
nursing staff who are working in the Ministry of Health and Ministry of Higher Education and Scientific
Research in the provinces of Erbil, Mosul and Kirkuk to determine the factors that affect their satisfaction.
Methodology:٨
descriptive design was carried-out from September 20, 2006 through April 1,'؛ 2007 in order
to assess the job satisfaction for nursing staff in governmental health agencies and educational setting.
Quantitative research methods were utilized to employ the study design. The study was conducted on three Iraqi
governorates (Mosul, Kirkuk, and Erbil). The sample of the study was collected
The success of any media work in our contemporary life is based on proper planning. Television in Iraq is like any media outlet that adopts clear planning and programming in order to achieve the goals set in the news, entertainment, education. Iraq TV relies on four programming plans in one year (short term), but we often receive central instructions directly from the Minister of Information ordering to cancel the program plan and what was scheduled for broadcast to be finally replaced by alternative or emergency program associated with an incident, occasion or important news, these programs are all called (emergency programs).
In this present research we will be dealing with these programs as well as the extent of their impact o
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Background: Although radiological diagnostic studies (RDS) are an important and acceptable part of medical practice, it is not without hazards. It is associated with increased risk of cancer. Unfortunately the typical and safe dose of each radiological examination is not known. Most of our knowledge of cancer risk comes from studies of survivors of those exposed to whole body radiation from atomic bomb in Hiroshima & Nagasaki, jobs associated with radiation exposure, Chernobyl survivors & patients treated with radiation therapy for cancer and other diseases.
Objectives To estimate radiation dose received by patients from diagnostic radiological examinations and lifetime
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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
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Background: The study's objective was to estimate the effects of radiation on testosterone-related hormones and blood components in prostate cancer patients. N Materials and Method: This study aims to investigate the effects of radiation on 20 male prostate cancer patients at the Middle Euphrates Oncology Centre. Blood samples were collected before and after radiation treatment, with a total dose of 60- 70 Gy, The blood parameters were analyzed. The hospital laboratory conducted the blood analysis using an analyzer (Diagon D-cell5D) to test blood components before and after radiation. Hormonal examinations included testosterone levels, using the VIDASR 30 for Multiparametric immunoassay system Results: The study assessed the socio-demogra
... Show More<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope
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Objective: To evaluate knowledge towards smoking and its relationship with lung cancer among members of
Baghdad Nursing College.
Methodology: The study comprised 100 affiliates from the College of Nursing/ University of Baghdad that
included students, teaching staff and employees. All data was collected through a structured questionnaire
prepared by the National Cancer Research Center which were answered during a scientific symposium
organized by the center on lung Cancer Awareness in March 2016.The data were analyzed by using the SPSS,
version 22
Results: The age of the respondents ranged from (19-64 years); 76% were females and only 4% were smokers.
The results showed that the mean score for the level of knowled