Preferred Language
Articles
/
bsj-7988
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
...Show More Authors

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.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Role of the Clinical Pharmacist in Reducing Preventable Adverse Drug Events
...Show More Authors

According to so many previous studies, lack of sufficient information during prescribing steps may lead to medication errors. Thus, the presence of the clinical pharmacist during routine rounding process in the ward with intervention of patient care plan may reduce the probability of adverse drug events (ADEs).This study evaluate role of the clinical pharmacists, as a member of medical team with the physician, on ADEs and report their interventions in the internal medicine unit. This study was designed to compare between two groups of patients, those receiving care from a rounding team (physician, nurse, and clinical pharmacist) (study or intervention group with 51 patient); and those receiving c

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
...Show More Authors

View Publication
Scopus (32)
Crossref (32)
Scopus Clarivate Crossref
Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
...Show More Authors

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
...Show More Authors

Scopus (23)
Crossref (17)
Scopus Clarivate Crossref
Publication Date
Tue Jun 03 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison of some artificial neural networks for graduate students
...Show More Authors

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

... Show More
View Publication
Crossref
Publication Date
Wed May 10 2017
Journal Name
Journal Of The College Of Languages (jcl)
Factores lingüísticos y extralingüísticos de la evolución semántica de los términos Linguistic and non-linguistic factors of the semantic evolution of terms
...Show More Authors

La disciplina sémantica siendo una rama de la lingüística y relacionada con los significados que residen detrás de los vocablos sería muy intereseante ser estudiada y investigada, sobre todo cuando tratamos de penetrarnos dentro de la evolución semántica y los motivos por los que se suceden estos cambios. Pues, es injusto dejar de dar una definición aclaratoria sobre esta disciplina y sus componentes.

El significado de los léxicos que se forma por un conjunto de semas o rasgos significativos mínimos. Sin embargo, no todos esos semas son igualmente intervenidos por los hablantes de una comunidad lingüística, sino que hay algunos de ellos que siempre están presentes, mientras que otros varían. Es decir, el significado

... Show More
View Publication Preview PDF
Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
...Show More Authors

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

... Show More
Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
...Show More Authors

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

... Show More
View Publication Preview PDF
Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Accounting Mining Data Using Neural Networks (Case study)
...Show More Authors

Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Dec 12 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Gender Differences in Adverse Drug Reactions Among Adult Patients Reported to the Iraqi Pharmacovigilance Center
...Show More Authors

For many years it was argued that there may be a gender differences in adverse drug reactions (ADRs). This assumption was based on many possible factors such as hormonal or behavior differences, and it was not clearly identified since the female gender was not preferred to be enrolled in many clinical trials. The primary aim of this study was to assess the extent of possibly relevant gender differences in drug–ADRs regarding causality, severity, preventability, seriousness, expectedness and outcome. While the secondary aim was to assess for which group of drugs and for which ADRs gender differences are identified most often. The study was a retrospective one that depends on processing a specially selected group of data obtained from th

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref