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Best Way to Detect Breast Cancer by UsingMachine Learning Algorithms
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Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with missing value and without
missing value, where the missing value is one attribute is missing from one sample
for data set. The test result is show SMO is the best algorithm, especiallywhen the
research removes the samples that contained the missing value.

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Publication Date
Sat Dec 30 2023
Journal Name
Al-kindy College Medical Journal
Radiological Significance of Shear-Wave Elastography Technique for Evaluation of Solid Breast Masses with Histopathological Correlation
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Background: Although various imaging modalities are available for evaluating suspicious breast lesions, ultrasound-based Shear-Wave Elastography (SWE) is an advanced, non-invasive technique complementary to grayscale sonography. This technique evaluates the elasticity of a specific tissue by applying sonic pressure to that tissue.

Objective: The aim is to assess the role of SWE in evaluating solid breast masses in correlation to histopathological study results.

Subjects and Methods: This prospective study was done in a tertiary care teaching hospital from September 2019 to August 2020. A study population of 50 women aged 18 years or above with an

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Publication Date
Sun Apr 26 2020
Journal Name
Iraqi Journal Of Science
Elucidative Histopathological Study in Female Cancer Patients: Histopathology in Female cancers
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Aims: Because of the high incidence of cancer in females, we need to identify an accurate therapy to deal with the treatment of different types and stages of cancer. Histopathology acts as an important step to foresee the stage in which the cancer is present, its risk of metastasis, and the health outcomes after completion of treatment. Histopathology grading acts as an important criterion to determine the treatment pattern to be adopted, the prognosis in patients and other possible future risks. Hence conducting novel histopathologcial studies in major female cancers is necessary in determining the treatment plan to be chosen for the patient.

Study design: Retrospective Observational study

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Publication Date
Sun Jul 01 2012
Journal Name
Eastern Mediterranean Health Journal
Knowledge and practices of women in Iraqi universities on breast self examination
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This study evaluated the knowledge and practice of breast self-examination (BSE), among a sample of educated Iraqi women. The study sample comprised 858 women aged 18–62 years affiliated to 6 major Iraqi universities, categorized according to occupation as teaching staff (11.5%), administrative staff (18.0%) and students (70.5%). Data were collected by a self-completed questionnaire. In all, 93.9% of the women had heard about BSE, the main source of information was television (39.9%), doctors (18.4%) and the awareness campaign of the Iraqi National Breast Cancer Research Programme (11.6%). Only 53.9% of the women practised BSE; the most common excuses by those that did not were lack of knowledge of the significance of BSE (42.0%) and lack

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Correlation Expression between P52 and BCL2 among Iraqi Women with Breast Carcinoma
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Publication Date
Sat Dec 01 2018
Journal Name
Annals Of Medicine And Surgery
Plasma d-dimer level correlated with advanced breast carcinoma in female patients
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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Transfer Learning Based Traffic Light Detection and Recognition Using CNN Inception-V3 Model
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Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
3-D Packing in Container using Teaching Learning Based Optimization Algorithm
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

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Publication Date
Thu Apr 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate Complete the Survival Function for Real Data of Lung Cancer Patients
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 In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Study of Malondialdehyde Levels in sera, RBCs and Tissues homogenate of Iraqi Women With Breast Tumors
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Breast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
King Khalid University towards Strategies Compatible with Brain-Based Learning (BBL)
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The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

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