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Design and evaluation of a new mobile application to improve the management of minor ailments: a pilot study
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Abstract<sec> <title>Background

Seeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.

Methods

The scientific content of the application was based on the information in the symptoms in the pharmacy and British National Formulary books. The design and content of the application were approved by two experts. Thereafter, the application was built for Android mobiles using flutter technology and dart language. A pre-post pilot study was conducted to assess outcomes associated with use of the application, including user acceptance and appropriateness of clinical recommendations. Fifteen students from the College of Pharmacy/University of Baghdad who had an Android mobile participated in this study. Two different scenarios about diarrhea were used during the pilot study, in which the researcher acted as a patient (SP) and the participant student as a pharmacist.

Results

After using the application, the number of questions asked by the participated student to the SP was significantly increased to about double. Additionally, providing the SP with appropriate non-pharmacological and pharmacological therapy along with optimum counseling and education were also significantly improved. All study participants agreed on the application’s ease of use and ability to reduce diagnosis and medication errors.

Conclusions

The implementation of the newly developed mobile application, diarrhea management step by step, was associated with improvements in assessment and recommended treatments for diarrhea cases with good acceptance by a pilot sample of pharmacy students at Baghdad University.

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Publication Date
Fri Nov 24 2017
Journal Name
Journal Of Engineering
A New Analytic Method to Tune a Fractional Order PID Controller
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This paper proposes a new method to tune a fractional order PID controller. This method utilizes both the analytic and numeric approach to determine the controller parameters. The control design specifications that must be achieved by the control system are gain crossover frequency, phase margin, and peak magnitude at the resonant frequency, where the latter is a new design specification suggested by this paper. These specifications results in three equations in five unknown variables. Assuming that certain relations exist between two variables and discretizing one of them, a performance index can be evaluated and the optimal controller parameters that minimize this performance index are selected. As a case study, a thir

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Ergodic Capacity for Evaluation of Mobile System Performance
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In this research the performance of 5G mobile system is evaluated through the Ergodic capacity metric. Today, in an­­y wireless communication system, many parameters have a significant role on system performance. Three main parameters are of concern here; the source power, number of antennas, and transmitter-receiver distance. User equipment’s (UEs) with equal and non-equal powers are used to evaluate the system performance in addition to using different antenna techniques to demonstrate the differences between SISO, MIMO, and massive MIMO. Using two mobile stations (MS) with different distances from the base station (BS), resulted in showing how using massive MIMO system will improve the performance than the standar

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Publication Date
Thu Oct 06 2011
Journal Name
Fes Journal Of Engineering Sciences
Derivation of a New Equation to Obtain the Permeability Coefficient of Clayey Soils
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Study of the Anticancer and Antimicrobial Biological Activity of a New Series of Thiohydantoin Derivatives
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Publication Date
Sat Mar 01 2025
Journal Name
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Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Sun Feb 10 2019
Journal Name
Drug Invention Today
Design, characterization, and in vitro evaluation of zaltoprofen solid dispersion as a hollow-type rectal suppository
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Aim: The present study aims to improve the poor water solubility of zaltoprofen which is a non-steroidal anti-inflammatory drug (NSAIDs) with a potent analgesic effect using solid dispersion then formulate it as a hollow type suppository to be more convenient for geriatric patients. Materials and Method: Zaltoprofen solid dispersions were prepared by solvent evaporation technique in different zaltoprofen: Soluplus® ratios. Results: Among the formulations tested, zaltoprofen solid dispersion preparation using 1:5 (zaltoprofen: Soluplus®) ratio showed the highest solubility and selected for further investigation. Solid dispersion characterization was evaluated by differential scanning calorimetry (DSC), X-ray diffraction study (XRD) and Fou

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Publication Date
Wed Jul 31 2019
Journal Name
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A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
A Unit Plan Based Upon The MI Theory: A theoretical study with an application Inside The Classroom
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This research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
"Acquired organizational immune and its impact on the application of knowledge management strategies" Analytical study of the opinions of a sample of Lecturer staff at the Technical College of Engineering and the Technical Institute of Amara
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Publication Date
Tue Aug 01 2023
Journal Name
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A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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