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A Novel Algorithm for Predicting Antimicrobial Resistance in Unequal Groups of Bacterial Isolates
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Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials. According to the proposed algorithm, the predicted resistance values were more valid than the observed values. This proposed algorithm is expected to help the hospital antibiotic policy committee recommend the proper antibacterial agents for S. Typhi and further bacterial isolates.

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Publication Date
Thu Aug 11 2016
Journal Name
Advanced Materials
Contact Resistance Effects in Highly Doped Organic Electrochemical Transistors
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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis, Characterization and Surface Properties of Nano-TiO2 Using a Novel Leaf Extracts
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    The main focus of research is on the nature of applications in the fields of science and technology, particularly nanotechnology. In this paper, a simple, non-toxic, inexpensive, and environmentally friendly green method was used to synthesize TiO2 nanoparticles using the extraction of portulacaria afra plant leaves and TiCl4 as a precursor. The synthesized titanium dioxide nanoparticles were characterized by scanning electron microscopy, atomic force microscopy, X-ray diffraction patterns, Fourier transform infrared spectroscopy, and Brunauer-Emmett-Teller analysis. The SEM image of TiO2 nanoparticles showed a few spherical, non-agglomerated particles. The average diameter of the nanoparticles, ac

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Publication Date
Tue Jun 01 2021
Journal Name
Jpras Open
The utility of a novel vacuum-assisted foreign body extraction technique from wounds
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Retained soft tissue foreign bodies following injuries are frequently seen in the Emergency and Plastic Surgery practice. The patients with such presentations require a watchful and detailed clinical as- sessment to overcome the anticipant possibility of missing them. However, the diagnosis based on the clinical evaluation is usually challenging and needs to be supported by imaging modalities that are suboptimal and may fail in identifying some types of foreign bodies. Owing to that, serious complications such as chronic pain, infection, and delayed wound healing can be faced that necessitate a prompt intervention to halt those detrimental consequences. The classical method of removal is a surgical exploration which is not free of risks.

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Wed Jan 24 2018
Journal Name
The Journal Of Physical Chemistry C
Novel Approach for Fabricating Transparent and Conducting SWCNTs/ITO Thin Films for Optoelectronic Applications
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Publication Date
Sun Aug 24 2014
Journal Name
Wireless Personal Communications
Multi-layer Genetic Algorithm for Maximum Disjoint Reliable Set Covers Problem in Wireless Sensor Networks
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sun Mar 01 2020
Journal Name
Computer Networks
An improved multi-objective evolutionary algorithm for detecting communities in complex networks with graphlet measure
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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Determination of Testosterone level as predictor for insulin resistance in young men with family history of type2 diabetes and hypertension.
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Background: Insulin resistance is associated with metabolic syndrome , type 2 diabetes and representing a risk factor for cardiovascular disease . This relationship may be modulated to some extent by age related changes in sex hormone status.. In particular, reduced total testosterone (TT) levels have been associated with insulin resistance and subsequent risk for developing type 2 diabetes. Aim of study: we examined whether low total testosterone level were associated with insulin resistance in young adult men. Methods: a total of 83 men (young adult men) divided into 2 group : (group1 ) 49 men with a risk factor for insu

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