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Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson correlation coefficient (PCC) are chosen from 10: Sex, Speech delay, Jaundice, Genetic disorders, and family history. Next, chosen ASD feature dataset through its paces using five ML techniques: Naive Bayes (NB), K-Nearest Neighbor (k-NN), Decision Tree (DT), Support Vector Machine (SVM), and AdaBoostM1 (ABM1). The proposed framework is assessed in the third phase utilizing five measurements such as accuracy, precision, predicting time, recall, and F1-score,. The findings revealed that: The NB and K-NN approaches exhibit superior accuracy rates of 99.2% and 97.2%, with minimal prediction times of approximately 0.3 seconds and 0.45 seconds, correspondingly. Conversely, the DT and AdBM1 methods demonstrate a minor decline in accuracy, achieving 94.8% and 87.6%, respectively, along with increased prediction times. Nonetheless, the SVM approach exhibits the least performance, achieving an accuracy of 80.4% with a highest prediction time of 0.84 seconds.</p>
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Publication Date
Sun May 11 2025
Journal Name
Journal Of Information Systems Engineering And Management
The Effect of the Learning Mastery Strategy using Interactive Learning Techniques as a Therapeutic Method on the Achievement of Secondary School Students in Mathematics
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  The current research aims to identify the effect of the learning mastery strategy using interactive learning as a therapeutic method on the achievement of secondary school students in mathematics. To achieve the research objective, the researcher selected second-grade middle school students at Al-Haybah Intermediate School for Boys and determined his research sample, which consisted of (77) students distributed into two sections: Section (A) the experimental group, with (38) students, and Section (B) the control group, with (39) students. The statistical equivalence of the two research sample groups was confirmed in the variables (intelligence test, previous achievement, and previous knowledge test). The researchers chose the par

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Mon Jun 27 2022
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Self-Reported Sleep Disorder, Anxiety and Depression in Iraqi Patients Post-Myocardial Infraction
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Background: Myocardial infarction (MI) is distinguished by the necrosis of myocardial cells as a result of substantial and prolonged ischemia. Anxiety, problems sleeping, and feelings of depression are some of the most common psychosocial consequences of having a myocardial infarction. Aim: The purpose of this study is to evaluate the effects of post-myocardial infarction on patients' levels of anxiety, depression, and quality of sleep. Method: The collection of data from 94 individuals with MI was carried out according to a descriptive cross-sectional design. Sleep quality, depression, and anxiety were evaluated using standard questionnaires. Results: 69.1% of the participants reported having trouble getting quality sleep. The perc

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Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Publication Date
Thu May 05 2022
Journal Name
Al-kindy College Medical Journal
Spinal Tuberculosis in Children
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Tuberculosis continues to be the leading cause of morbidity and mortality, with an estimated annual incidence of 10.4 million worldwide. It has been estimated that 10% of patients with extrapulmonary tuberculosis have musculoskeletal involvement, with the spine being the most common. Spinal tuberculosis (TB) accounts for 50% of cases of musculoskeletal tuberculosis.

Spinal tuberculosis is the result of infection with Mycobacterium tuberculosis. It is a secondary infection, the primary lesion of which is in the lungs, genitourinary system, or gastrointestinal tract and can be active or latent. Involvement of the vertebral segment is the result of hematogenous spread of infection along the arterial pathway or Batson's vei

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

<

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Publication Date
Wed Jan 01 2014
Journal Name
Biochemical Cellular Archive
The relationship between helicobacter pylori infection and reproductive disorder
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To determine the relationship between infertility and Helicobacter pylori infection, thirty-five infertile patients of ages (20-49) years have been investigated and compared with 10 apparently firtility individuals. All the studied groups were carried out to measure (ASA), (TNF-á), (IL-6), (anti-H.pylori IgA) and (anti-H.pyloriIgG) by Enzyme linked immunosorbent assay (ELISA) technique. The statistical analysis also demonstrated that there were a highly significant differences (P<0.01), when compared between studied group. Also, the statistical analysis demonstrated that there were a highly significant differences (P<0.01) when compare between infertility and fertility in Conc. of sperm. The percentage distribution of ASA in serum and seme

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Tue Jan 01 2013
Journal Name
Innovative Systems Design And Engineering
Automated Surface Defect Detection using Area Scan Camera
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