Objective(s): To evaluate and compare between Health Promotion Program for the Prevention of Epidemics at Primary Health Care Centers in Baghdad City.

Methodology: A descriptive study, using the evaluation and comparative approaches, is conducted to evaluate health promotion program for the prevention of epidemics at primary health care centers in baghdad city from October 15^th  2019 through March 1^st 2020. A purposive, non-probability, sample of (42) health promotion unit officers were recruited from the same number of primary health care centers which were divided into (14) main, (14) sub and (14) family medicine primary health care centers i

Background: Menopause can bring oral health problems and also associated with significant adverse changes in the orofacial complex. After menopause, women become more susceptible to periodontal disease due to deficiency of estrogen hormone. Current study aimed to evaluate the periodontal health status in relation to salivary constituent including pH, flow rate and some elements (Magnesium, Calcium and inorganic phosphorus) of pre and post-menopause women. Materials and Methods: Periodontal health status of 52 women aged 48-50 years old (26 pre-menopause and 26 post-menopause) were examined including (gingival index, plaque index, calculus index, probing pocket depth and clinical attachment level). Salivary sample was collected for two women

Background: Antibiotic resistance is a problem leading to difficulty in treating microbial infections thatmay occur due to many causes. For the important pharmacist role as a reference for the information and theability to access to medications, they are vital members in lowering the development of antibiotic resistance,and also they support the proper use and control of antibioticsmisuse. Our goal is comparing the knowledge,attitude, practice of undergraduate and postgraduate pharmacy students and their perceptions about thecausing factors of antibiotic resistance in Iraq.Method: A cross sectional study was conducted involving the final year bachelor and postgraduate (masterand Philosophical doctor) students from different private

Background: Pyogenic discitis most frequently occurs
after home delivery, hemorridectomy, and dilatation and
curettage. Discitis is generally due to blood borne bacterial
invasion of the disc from adjacent end-plate via
communicating vessels. Infective discitis remains an
uncommon, but potentially serious cause for back pain.
Delayed diagnosis can occur and a high index of suspicion
may occur.
Methods: The study included 30 patients suffering from
localized low back pain with limitation of movement.
Diagnosis was made by history, physical examination and
investigation mainly E.S.R and MRI.
Results: 50.3% of patient with discitis had a history of
vaginal delivery, 15% had a history of hemorridectomy

The research aims to identify the relationship between employing future skills during teaching from the viewpoint of students of Islamic studies at the Northern Border University, as well as their attitudes towards future professions. The researcher employed the correlational descriptive approach. The tools were a questionnaire for employing future skills, and a scale for the attitude towards the future profession. The two research tools were applied to a random sample of (242) male and female students from the department of Islamic Studies, College of Education and Arts. The findings showed that the total level of employing future skills and their three axes during teaching was average. It was also found that the attitude towards future

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