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Model for Prediction of the Weight and Height Measurements of Patients with Disabilities for Diagnosis and Therapy
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Background: Accurate measurement of a patient’s height and weight is an essential part of diagnosis and therapy, but there is some controversy as to how to calculate the height and weight of patients with disabilities. Objective: This study aims to use anthropometric measurements (arm span, length of leg, chest circumference, and waist circumference) to find a model (alternatives) that can allow the calculation of the height and the body weight of patients with disabilities. Additionally, a model for the prediction of weight and height measurements of patients with disabilities was established. Method: Four hander patients aged 20-80 years were enrolled in this study and divided into two groups, 210 (52.5%) male and 190 (47.5%) female. Result: A significant correlation was noted between body height and arm span, as well as between body height and length of leg in all study groups. The body weight and the ratio of arm span or leg length to the sum of chest and waist circumferences were found to have a negative significant correlation. Model equations were derived to estimate the height and body weight according to anthropometric measurements. Conclusion: Anthropometric measurements can be used to create a model for calculating the body height and body weight of patients with disabilities and which can be considered an alternative to measurements that can be made on otherwise healthy subjects.

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Publication Date
Fri Dec 06 2019
Journal Name
Karbala International Journal Of Modern Science
Stereo Photogrammetry vs Computed Tomography for 3D Medical Measurements
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Publication Date
Sun Jul 25 2021
Journal Name
Natural Resources Research
Effect of Water Flooding on Oil Reservoir Permeability: Saturation Index Prediction Model for Giant Oil Reservoirs, Southern Iraq
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Skills and Standards of Selection and Use of Assistive Technology among Saudi Teachers of Students with Intellectual and Developmental Disabilities
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The purpose of the current study was to explore the standards that teachers take into consideration when selecting and using assistive technology (AT), in addition to their knowledge and skills in this area. A quantitative, descriptive survey design was used and a convenience sample of 79 teachers of students with intellectual disabilities and autism spectrum disorder (ASD) participated in the current study. Based on the four main areas of the SETT Framework—student, environment, tasks, and tools—, teachers reported a lack consideration for most of the standards in each area. Among other findings, statistically significant differences were found between teachers’ standards of the SETT Framework, with teachers who had previous profe

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Adherence and Beliefs to Adjuvant Hormonal Therapy in Patients with Breast Cancer: A Cross-Sectional Study (Conference Paper) #
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  Breast cancer is the most common cancer among women over the world. To reducing reoccurrence and mortality rates, adjuvant hormonal therapy (AHT) is used for a long period. The major barrier to the effectiveness of the treatment is adherence. Adherence to medicines among patients is challenging. Patient beliefs in medications can be positively or negatively correlated to adherence. Objectives: To investigate the extent of adherence and factors affecting adherence, as well as to investigate the association between beliefs and adherence in women with breast cancer taking AHT. Method: A cross-sectional study included 124 Iraqi women with breast cancer recruited from Middle Euphrates

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Publication Date
Wed Jun 01 2022
Journal Name
Political Sciences Journal
The Problem of Political Empowerment of Women with Disabilities in Light of Iraqi Legislation
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Democracy in any country is measured by the cultural, social and economic level reached by women in it in general and women with disabilities in particular, and the extent of their participation in political life and political decision-making. As a result of the patriarchal power that societies have known, including Iraq, history has witnessed multiple types and forms of discrimination against women, which differed from one country to another, this matter has pushed women and since the beginning of the last century the issue of women's rights has been raised at the global, regional and national levels, through holding international conferences and agreements In order to empower women in all social, economic and political fields.

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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Medical Research & Health Sciences
Assessing the Period between Diagnosis of Breast Cancer and Surgical Treatment among Mastectomized Female Patients in Iraq
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Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level

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Publication Date
Tue Jan 09 2018
Journal Name
International Journal Of Medical Research & Health Sciences
Assessing the Period between Diagnosis of Breast Cancer and Surgical Treatment among Mastectomized Female Patients in Iraq
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Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

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