Objective: To find out if there are any significant differences between these women's knowledge in the
management of Breast Self-Examination in study and control group regarding some variables.
Methodology: A quasi-experimental design was used. A purposive "non-probability" sample of (260) women who
are employee and students in both colleges (Nursing and Health and Medical Technologies) was selected. The
sample consists of two groups, experimental group (130) includes those in (Nursing college), and control group
(130) in (Health and Medical Technologies). A questionnaire was constructed which included demographic
information, reproductive information, family history, previous medical history, and information about women's
knowledge in managing breast-self examination (BSE). Data were collected through the use of the questionnaire, the
application of the educational program. A post-test was done for the study only which uses the lectures, booklet,
training practices of BSE, and video film. Data analysis was performed through the application of descriptive and
inferential statistical approaches.
Results: There are significant associations between women's knowledge regarding managing BSE and their marital
status, infertility status, lactation and second degree consanguinity; also the study concluded that the educational
program of BSE is necessary for all women in different age groups, with different medical histories, educational
level, occupational status, and considered as an effective mean for the reinforcement of improvement of women's
knowledge regarding managing BSE.
Recommendations: Implementation of proposed model of continuous medical education for women for BSE within
the scope of their work.
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
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