Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculated with risk mortality at 5 and 10 years depending on the number of unknown factors. The new system presented in a graphical user interface to facilitate the friendliness at the user side.
Introduction: Breast cancer is a significant global health concern, affecting millions of women worldwide. While advancements in diagnosis and treatment have improved survival rates, the impact of this disease extends beyond physical health. It also significantly influences a woman's lifestyle and overall well-being. Objectives: The current study intends to analyze the lifestyle of breast cancer patients who are receiving therapy or are being followed up at the Oncology Teaching Hospital in Medical City, Baghdad, Iraq. Method: The present study uses a descriptive design with an application of an evaluation approach. A convenience sample of 100 women with breast cancer was selected from the Teaching Oncology Hospital at the Medical C
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Objective(s): To determine the impact of psychological distress in women upon coping with breast cancer.
Methodology: A descriptive design is carried throughout the present study. Convenient sample of (60) woman with breast cancer is recruited from the community. Two instruments, psychological distress scale and coping scale are developed for the study. Internal consistency reliability and content validity are obtained for the study instruments. Data are collect through the application of the study instruments. Data are analyzed through the use of descriptive statistical data analysis approach and inferential statistical data analysis approach.
Results: The study findings depict that women with breast cancer have experien
... Show MoreObjective: Evaluation of women's knowledge about risk factors and early detection of breast cancer at
Ibn Rushd college of education in Baghdad University.
Methodology: The study sample included (184) women in the Ibn Rushd College / University of
Baghdad, whose age ranged between (17-58) years. Data were collected through a structured
questionnaire prepared by the National Cancer Research Center which were answered during a scientific
symposium about breast cancer. The score was calculated by correcting the results of the answer, giving
one score for each correct answer and then estimating the level of knowledge and inputting all data in a
statistical program.
Results: The results showed limited level of women's
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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Background:-The Modified Alvarado Scoring
System (MASS) has been reported to be a cheap
and quick diagnostic tool in patients with acute
appendicitis. However, differences in diagnostic
accuracy have been observed if the scores were
applied to various populations and clinical settings.
Objectives:- The purpose of this study was to
evaluate the diagnostic value of Modified Alvarado
Scoring System in patients with acute appendicitis
in our setting.
Methods:-one hundre twenty eight patients, were
included in this study, admitted to Al-Kindy
teaching hospital from June 2009 to June 2010.
Patients’ age ranged from 8 to 56 years (21±10)
they were divided into three groups; paediatrics,
child bear
Background:-The Modified Alvarado Scoring System (MASS) has been reported to be a cheap and quick diagnostic tool in patients with acute appendicitis. However, differences in diagnostic accuracy have been observed if the scores were applied to various populations and clinical settings.
Objectives:- The purpose of this study was to evaluate the diagnostic value of Modified Alvarado Scoring System in patients with acute appendicitis in our setting.
Methods:-one hundre twenty eight patients ,were included in this study, admitted to Al-Kindy teaching hospital from June 2009 to June 2010. Patients’ age ranged from 8 to 56 years (21±10) they were divided into three groups; paediatrics, child bearing age females & adult males,. MAS
The current study was conducted in the period extending from November 2018 to October 2019 and designed as a case-control study and aimed to assess the seroprevalence of HCMV. However, a total number of 91serum specimens were collected to fulfill this purpose from females (71 breast cancer patients, and control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital and the practical part was performed in College of Science, University of Baghdad. The study protocol was approved by the Ethics Committee at the Department of Biology (Reference: BEC/0220/0011). The immunological part for evaluation of seroprevalence of HCMV was accomplished by ELISA technique which revealed that anti-HCMV IgG was sco
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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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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