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A clinical-statistical study on COVID-19 infection and death status at the Alshifaa Healthcare Center/ Baghdad
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Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 were infected and the rest of them were not. Results: The study showed that males’ infection and death cases were higher than females by more than double, despite the population ratios of the two genders being almost equal. Furthermore, as the age of patients is older, the chance of death is higher. Death cases were lower in December than the previous three months, which could be attributed to lower infection cases compared with the previous months. Conclusions: We can conclude that the peak of infected ages was the same as the other countries. Hence, the number of checked children was low, while we have the peak around the 40s and 50s. Females’ death cases were much less than males, which could be attributed to the genetic influence and the higher responsibility that females showed than males to prevent the disease’s spreading.

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Publication Date
Thu Sep 03 2020
Journal Name
Journal Of Public Affairs
Ethnographic research method for psychological and medical studies in light of COVID ‐19 pandemic outbreak: Theoretical approach
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Ethnographic research is perhaps the most common applicable type of qualitative research method in psychology and medicine. In ethnography studies, the researcher immerses himself in the environment of participants to understand the cultures, challenges, motivations, and topics that arise between them by investigating the environment directly. This type of research method can last for a few days to a few years because it involves in-depth monitoring and data collection based on these foundations. For this reason, the findings of the current study stimuli the researchers in psychology and medicine to conduct studies by applying ethnographic research method to investigate the common cultural patterns language, thinking, beliefs, and behavior

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for New COVID-19 Cases Using Recurrent Neural Networks and Long-Short Term Memory
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     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470

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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Impact of SARS-COV-2 Variants on the Infection Severity among Iraqi Patients
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     Severe acute respiratory corona viruses (SARS-COVs) are a particular category of RNA viruses that have emerged as a potential danger to the human population, triggering epidemics and pandemics that have resulted in catastrophic human mortality. The SARS-CoV2, responsible for the COVID-19 pandemic that began on December 12, 2019 in Wuhan, China, has been linked to bats. A new SARS-CoV-2 variant appeared in late December 2020. Mutations with variants continued to appear until the time of this study. Thus, this study aimed to provide a local database among Iraqi patients about SARS-COV-2 variants as there have been very few local studies documenting its existence and its relationship with the progression and severity of infection.

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Spatio-Temporal Mixture Model for Identifying Risk Levels of COVID-19 Pandemic in Iraq
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     This paper focuses on choosing a spatial mixture model with implicitly includes the time to represent the relative risks of COVID-19 pandemic using an appropriate model selection criterion. For this purpose, a more recent criterion so-called the widely Akaike information criterion (WAIC) is used which we believe that its use so limitedly in the context of relative risk modelling. In addition, a graphical method is adopted that is based on a spatial-temporal predictive posterior distribution to select the best model yielding the best predictive accuracy. By applying this model selection criterion, we seek to identify the levels of relative risk, which implicitly represents the determination of the number of the model components o

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
COVID-19 Detection via Blood Tests using an Automated Machine Learning Tool (Auto-Sklearn)
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     Widespread COVID-19 infections have sparked global attempts to contain the virus and eradicate it. Most researchers utilize machine learning (ML) algorithms to predict this virus. However, researchers face challenges, such as selecting the appropriate parameters and the best algorithm to achieve an accurate prediction. Therefore, an expert data scientist is needed. To overcome the need for data scientists and because some researchers have limited professionalism in data analysis, this study concerns developing a COVID-19 detection system using automated ML (AutoML) tools to detect infected patients. A blood test dataset that has 111 variables and 5644 cases was used. The model is built with three experiments using Python's Auto-

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Publication Date
Wed Feb 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
A Comparative Study between Computer Textbooks Content in the Secondary Stage and Computer Textbooks Content in the University Stage in Colleges of Education at Baghdad University
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Record, verify, and showcase your peer review contributions in a format you can include in job and funding applications (without breaking reviewer anonymity).

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Publication Date
Wed Dec 01 2010
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Statistical study for Indian quasi-stable population
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During more than (50) years past, India has achieved considerable social and economic progress. It is also generally assumed that the future progress will be even more rapid and that India will be an important player in the global market. India has only (2.5) percent of global land whereas it has to provide home for one-sixth of world's population .On examining the past trends of India's population ,it may be observed that during the latter half of the twentieth century ,about (650) million populations were added to the country ,thus living in a country with a high population density and high growth rate , India in need a transition from high fertility high mortality to a low fertility low mortality and towards stable population situatio

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
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The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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Publication Date
Fri Dec 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Oral Health Condition and Nutritional Status among Cleft Lip and Palate in Baghdad-Iraq
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Background: Orofacial cleft is the most common craniofacial birth defect and the fourth most common congenital malformation in humans that have an effect on oral health in addition to nutrient intake affected in those children. This research aims to investigate gingival condition, dental caries experience and nutritional status among children with orofacial cleft and compare them with normal children. Materials and methods: The study group included 36 children with an age ranged (4-9) years of orofacial cleft. The control group included 37 children matched the control group in age and gender. Gingival condition measured by Gingival Index (Löe and Silness, 1963), while dental caries status was measured by (D1-4MFs/d1-4mfs) index according

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