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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
Sat Aug 31 2024
Journal Name
Folia Medica
Dental plaque caries related microorganism in relation to demographic factors among a group of Iraqi children
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Introduction: Streptococcus mutans and lactobacilli are most important bacteria in the pathogenesis of dental caries. Cariogenic microflora has been associated to the primary caregiver transmission and sugary diets.

Aim: This study aimed to relate S. mutans and lactobacilli in the plaque to demographic factors in Iraqi children.

Materials and methods: The study included 135 children aged 3-10 years. Samples of their dental plaque were taken from the upper second primary molars on the buccal surfaces using a clean toothpick. Each sample was stored in 1 ml of n

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Anemia and The Level of IL-6 in Children Infected with Entamoeba histolytica and Giardia lamblia
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The relation between anemia and inflammatory immune response has lately had much attention. This research was conducted from October 2018 until April 2019, including  (110) children below 12 years from both gender in some Hospitals, Primary Health care centers, Public Primary Schools and Kindergarten in Baghdad, Iraq. The objective of this study is to determine the possible correlation between iron deficiency anemia and inflammatory immune response  among children infected with Entamoeba  histolytica or Giardia  lamblia. Blood samples were taken from all groups to measure  hemoglobin level, serum iron, total iron binding capacity (TIBC), mean corpuscular volume (MCV), and mean corpuscular  hemoglobin concentration

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Publication Date
Wed Jan 15 2025
Journal Name
Dentistry 3000
Salivary Caries-Related Microorganisms and Demographics of a Group of Children
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Objective: The purpose of this study was to determine the association between caries related microorganisms in children’s saliva, such as Streptococcus mutans and lactobacilli, and their demographic factors. Methods: This study involved a sample of 135, both sexes with an age range between 3 and 10 years. Unstimulated saliva was obtained and diluted in normal saline. Saliva was then placed in selective media. Salivaris agar was used for mutans streptococci while Rogosa agar for lactobacilli. After incubation, Streptococcus mutans counting of CFU (colony forming units) with morphology characterization and numbers of CFU per milliliter of saliva for lactobacilli. Demographic factors information was collected using a questionnaire.

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Parents’ Knowledge about Nutritional Management of children with Phenylketonuria
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Abstract

Objective(s): to Evaluation of Parents’ Knowledge about Nutritional Management of kids with Phenylketonuria; to Identify the association between parents’ Knowledge about nutritional management then their demographic variables of fathers, mothers (parents age, residence then socioeconomic position).

Methodology: A non-experimental project; was accompanied on parents of phenylketonuria kid in Baghdad town since the period 3 June to 5 October 2022. A Non-probability sample (convenience) of 35 PKU children and their parents (father and mother) was selected Purposively from the hospitals that are select for the study. A survey is built for the purpose of the educa

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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Detection of Some Active compounds and Vitamins Increasing in Aloe vera Callus culture
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This study was aimed to use plant tissue culture technique to induce callus formation of Aloe vera on MS. Medium supplied with 10 mg/l NAA and 5 mg/l BA that exhibit the best results even with subculturing. As the method of [1] 1g. dru weight of callus induced from A. vera crown and in vivo crown were extracted then injected in HPLC using the standards of Ascorbic acid (vit. C), Salysilic acid and Nicotenic acid (vit. B5) to compare with the plant extracts. Results showed high potential of increasing some secondary products using the crown callus culture of A. vera as compared with in vivo crown, Ascorbic acid was 1.829 ?g/l in in vivo crown and increased to 3.905 ?g/l crown callus culture . Salysilic acid raised from 3.54 ?g/l in in vivo c

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
Seroprevalence and Molecular Detection of Human Parvovirus B19 in Beta Thalassemia Major Patients
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Beta thalassemia major (BTM) is a genetic disorder that has been linked to an increased risk of contracting blood-borne viral infections, primarily due to the frequent blood transfusions required to manage the condition. One such virus that can be transmitted through blood is the Human Parvovirus B19 (B19V). The aim of this study was to investigate the frequency and molecular detection of B19V. This study included 60 blood donors as controls and 120 BTM patients. B19V was identified by serology, which measured B19-IgG and B19-IgM antibodies. Nested Polymerase Chain Reaction (nPCR) was employed to target the VP1/VP2 structural proteins. The results showed that B19V seropositivity represents 27.5% (33 out of 120) in BTM patients, and

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Publication Date
Wed Feb 06 2019
Journal Name
National Academy Science Letters
The Detection Limit of PCR Amplification for Cryptosporidium spp. Oocysts in Fecal Samples
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Publication Date
Mon Jun 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Molecular Detection of High-Risk Human Papillomavirus Genotypes from Cervical Lesions in Baghdad
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Objective Using two complementary techniques of virus detection human papillomavirus (HPV)[capture of hybrids (CH) and polymerase chain reaction (PCR)], relate the cytological study and/or cervical biopsy with high-risk HPV (HPV-HR) genotypes presence, as well as relating their viral load (VL). Methods About 272 women, who presented most cell alterations compatible with lesions cervical HPV, which has been detected in all high risk by the CH method and HPV genotype detection by PCR. Results In 22% of the patients it was not detected HPV DNA. Genotype 16 and/or 18 was prevalent and was found in 33% of the 212 women studied, meanwhile, mixed infections were found by several genotypes in 25%. In as for the histological lesions found, in 61 pat

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