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Association between Enhancing Learning Needs and Demographic Characteristic of Patients with Myocardial Infarction: العلاقة بين تعزيز احتياجات التعلم والخصائص الديموغرافية لمرضى احتشاء عضلة القلب
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Abstract

Objectives: To find out the association between enhancing learning needs and demographic characteristic of (gender, education level and age).

Methods: This study was conducted on purposive sample was selected to obtain representative and accurate data consisting of (90) patients who are in a peroid of recovering from myocardial infarction at Missan Center for Cardiac Diseases and Surgery, (10) patients were excluded for the pilot study, Data were analyzed using descriptive statistical data analysis approach of frequency, percentage,  and analysis of variance (ANOVA).

Results: The study finding shows, there was significant relationship between gender and patients’ learning needs in pretest and posttest at (P value > .000), while no significant relationship was found with patients’ age and level of education with their learning needs.

Recommendations: The study recommend that the future research on perceived learning needs could focus at the needs of patients from other groups, such as individuals with cardiac arrhythmia but no MI. Further research into the perceived learning needs of these patient populations could be conducted.

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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Impact of Deep Learning Strategy in Mathematics Achievement and Practical Intelligence among High School Students
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— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen

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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Thu Nov 16 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Evaluating TLR4 Gene Expression to Monitor Disease Progression in Iraqi Patients with Rheumatoid Arthritis
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Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN

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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
White Spot Lesions Among Patients Treated With Fixed Orthodontic Appliance at Different Time Intervals
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ABSTRACT Background:- White spot lesions are common esthetic problem that compromise the success of orthodontic treatment. This study aimed to assess white spot lesions in patients with fixed orthodontic appliance at different time intervals. Materials & Methods:- Thirty two patients (24 females and 8 males) were included in this study and they underwent clinical examination for white spot lesions using enamel decalcification index at four time intervals: (2-3 weeks after appliance insertion, 2, 4 and 6 months). Results:- The patients were free of white spot lesions at the appliance insertion visit. The mean of white spot lesions was 2.22 which were increased significantly during six months to reach 24.59 at the end of study. There was a si

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Publication Date
Tue Jan 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Nephrotic range proteinuria; does it predict lung involvement in patients with type 2 diabetes
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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Biochemical Study on Anti Thyroid Peroxidase in Type 2 Diabetic patients with thyroid disorders
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Type 2 diabetes mellitus (T2DM) is the most frequent endocrinal disease commonly associated with thyroid disorders .The study is conducted at the Specialized Center for Endocrinology and Diabetes in Baghdad ,during December 2014 up to October 2015.This study was done to investigate the prevalence of anti- thyroid peroxidase (Anti-TPO) antibody in patients suffered from type 2 diabetes with thyroid disorders .The study groups included a total number of 80 subjects consisting of 60 type 2 diabetic patients divided into 20 hyperthyroidism subjects (group 1) ,20 hypothyroidism subjects (group 2), 20 euthyroidism subjects (group 3) and 20 healthy controls (group 4) . The fasting blood samples were analyzed for (T3,T4,TSH) by using Vitek Immuno d

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Sat Jun 18 2022
Journal Name
International Journal Of Health Sciences
E-learning applications and their significance among students of the Department of Chemistry in the Faculty of Education for Pure Sciences – Ibn Al-Haytham
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--The objective of the current research is to identify: 1) Preparing a scale level for e-learning applications, 2) What is the relationship between the applications of e-learning and the students of the Department of Chemistry at the Faculty of Education for Pure Sciences/ Ibn Al-Haytham – University of Baghdad. To achieve the research objectives, the researcher used the descriptive approach because of its suitability to the nature of the study objectives. The researcher built a scale for e-learning applications that consists of (40) items on the five-point Likrat scale (I agree, strongly agree, neutral, disagree, strongly disagree). He also adopted the scale of scientific values, and it consists of (40) items on a five-point scale as wel

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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