Objective: The study aims to assess the knowledge and practices of mothers with hemophilia children type - A - ,
socio-economic status and association between mother demographic information with their knowledge and practices
toward their children in Azadi Teaching Hospital in Kirkuk.
Methodology: Descriptive study no probability (purposive) sample. Selected Fifty-five of mothers having hemophilia
children, started from November 2012 to May 2013. Study was carried out in the Azadi teaching hospital in
Kirkuk. By using questionnaire which consists from five parts include demographic characteristics for mother and
children, socio-economic, Knowledge and practices data gathered, by direct interview with the mothers in the
hospital. Reliability and content validity of questioner were identified form of the pilot study. Descriptive and inferential
statistical used to analysis of data.
Results: The results of the study (30.9%) of the mothers were aged (40 - 44) and (43.6%) were graduates from primary
school. And their hemophilia children in all sample sex male, (41.8%) of hemophilia children were aged between
(5-9) years though (30.9 %) are not in school and that (69.1%) of the families have one child hemophilia infected
and (27.6%) were diagnosis bleeding in joint , level of severity of the disease (65.5%) was moderate
,(98.2%) of family depended on hospital to provide factor eight and other treatment to hemophilia child when
bleeding. socio – economic status of family show ( 61.8%) low status. (83.6%) of mothers uncertain of their information
about hemophilia, mother practices were (72.7%) sometimes and (23.6%) never done good practice to
their hemophilia children.
Recommendations: Develop special booklet for mothers local languages (Kurdish , Turkish ) develop programs and
awareness courses (theoretical and practical) for mothers and support family financial improve and provide factor
eighth for hospitals and health center where patients found.
Mammography 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
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