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Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.

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Publication Date
Fri Jun 11 2021
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of composite bonding spot size and location on the performance of poly-ether-ether-ketone (PEEK) retainer wires
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Background: Poly-ether-ether-ketone(PEEK) has been introduced to many dental fields. Recently it was tested as a retainer wire‎ following orthodontic treatment. This study aimed to investigate the effect of changing the bonding spot size and location on the performance of PEEK retainer wires. Methods: A biomechanical study involving four three-dimensional finite element models was performed. The basic model was with a 0.8 mm cylindrical cross-section PEEK wire, bonded at the center of the lingual surface of the mandibular incisors with 4 mm in diameter composite spots. Two other models were designed with 3 mm and 5 mm composite sizes. The last model was created with the composite bonding spot of the canine away from the center

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Publication Date
Sun Jul 01 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
GENOTYPE VERSUS PHENOTYPE TO DETERMINE THE DEFINITIVE IDENTIFICATION OF THE GENERA CHLORELLA BEIJERINCK, 1890 (CHLORELLACEAE) AND COELASTRELLA CHODAT, 1922 (SCENDESMACEAE)
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    Conventional identification of three coccoid green algae isolates was attempted to characterize the studied algae morphologically under compound microscope, which demonstrated confusional phenomenal convergence; all were classified microscopically as the green alga Chlorella vulgaris Beijerinck, 1890.

 

    Phylogenetic studies were conducted to settle the argument about the phenotype by studying the genotype. Genotype the promising field in advance classification by using 18S rRNA and compared to GenBank database using to search the related sequences. The determined sequences showed high a similarity to the strains registered in GenBank.

 

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Publication Date
Mon Jul 01 2024
Journal Name
Russian Journal Of Organic Chemistry
Synthesis and Study of the Biological Activity of New Compounds Derived from 4-(5-Phenyl-1,3,4-oxadiazole-2-yl)aniline
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Publication Date
Fri Mar 07 2025
Journal Name
Jurnal Keperawatan Soedirman
THE EFFECTS OF MUSIC INTERVENTIONS ON CHILDREN'S PAIN SEVERITY AND ANXIETY DURING DRESSING CHANGES IN IRAQ: A RANDOMIZED CONTROLLED TRIAL
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Abstract Daily dressing changes cause distress and pain for victims of burn injuries. The study aimed to determine the effect of music in reducing the pain and anxiety of thermally burned children during routine dressing changes. This quantitative study employed a randomized controlled trial design. The participants comprised 80 children at the Specialized Burns Hospital, in Baghdad, Iraq who were divided into two groups. The intervention group were exposed to three generic musical pieces (children’s music, nature sounds, and classical music) for 10-15 minutes. The researchers used the Objective Pain Scale, State-Trait Anxiety Inventory, and physiological parameters to measure the children’s responses immediately before the dressing cha

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Publication Date
Mon Jan 01 2024
Journal Name
Dyes And Pigments
3′,3′,4′,4′,5′,5′,6′,6′,6′-nonafluoro-hexyloxy groups substituted phthalocyanines: Synthesis, characterization and their biological properties
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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
The Impact of using the Internet and Social Media on Sleep in a group of Secondary School Students from Baghdad
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Background: Insufficient sleep due to excessive media use is linked to decrease physical activity, poor nutrition, obesity, and decreased overall health-related quality of life.

Objectives: To assess the effect of using the internet and social media on the sleep of 4th-stage secondary school students.

Subjects and Methods: Cross-sectional study with the analytic element; for 500 secondary school students, obtained by choosing two schools randomly from each of the six educational directorates, by using a structured questionnaire.

Result: Secondary scho

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Publication Date
Mon Dec 15 2025
Journal Name
Bionatura Journal: Ibero-american Journal Of Biotechnology And Life Sciences
Fourteen Years of Organic Amendments Enhance Soil Organic Carbon in Semiarid Iraqi Soils: FTIR Spectroscopy, PLS Modelling and RothC Simulations
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Long-term organic amendments are a key strategy to build soil organic carbon (SOC) stocks in semiarid agroecosystems, where low biomass inputs and calcareous parent material constrain carbon accumulation. This 14-year field experiment in central Iraq (2000–2014) evaluated how a gradient of organic matter (OM) additions (0, 1, 2.5, 5, 10, and 20%) affects SOC dynamics, nutrient availability, and soil organic matter composition in clay-dominated, semiarid soils. Surface and subsurface samples (0–30, 30–60, and 60–90 cm) were analysed for SOC, nutrients, and mid-infrared Fourier transform infrared (FTIR) spectra, which were then integrated with Partial Least Squares (PLS) regression and RothC simulations. Moderate OM inputs (5

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Publication Date
Mon Feb 24 2025
Journal Name
Polymers
Inducing Osteogenesis in Human Pulp Stem Cells Cultured on Nano-Hydroxyapatite and Naringin-Coated 3D-Printed Poly Lactic Acid Scaffolds
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Background: Regeneration dentistry demonstrates significant challenges due to the complexity of different dental structures. This study aimed to investigate osteogenic differentiation of human pulp stem cells (hDPSCs) cultured on a 3D-printed poly lactic acid (PLA) scaffold coated with nano-hydroxyapatite (nHA) and naringin (NAR) as a model for a dental regenerative. Methods: PLA scaffolds were 3D printed into circular discs (10 × 1 mm) and coated with nHA, NAR, or both. Scaffolds were cultured with hDPTCs to identify cellular morphological changes and adhesion over incubation periods of 3, 7, and 21 days using SEM. Then, the osteogenic potential of PLA, PLA/nHA/NAR, or PLA scaffolds coated with MTA elutes (PLA/MTA scaffolds) were evaluate

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Publication Date
Sat Jun 01 2013
Journal Name
مجلة كلية بغداد للعلوم الاقتصادية الجامعة
Proposed family speech recognition
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Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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