Preferred Language
Articles
/
IBjvG5YBVTCNdQwC6oKb
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
...Show More Authors

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep learning multigenetic features (MDL-MG) architecture incorporates a custom attention mechanism (CAM), bidirectional long short-term memory (BLSTM), and convolutional neural networks (CNNs). Additionally, the model was optimized to handle contrastive loss by extracting distinguishing features using a Siamese network (SN) architecture with a Euclidean distance metric. To assess the effectiveness of this approach, various evaluation metrics were applied to the cancer genome atlas (TCGA-BREAST) dataset. The model achieved 100% accuracy and demonstrated improvements in recall (16.2%), area under the curve (AUC) (29.3%), and precision (10.4%) while reducing complexity. These results highlight the model's efficacy in accurately predicting cancer survival rates.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Jul 05 2018
Journal Name
International Journal Of Medical Research & Health Sciences
Methicillin-Resistant Staphylococcus epidermidis Isolated from Breast Tumors of Iraqi Patients
...Show More Authors

Background: Globally, breast cancer is the second leading cause of death among women in Iraq. Several genetic and environmental factors are associated..

View Publication Preview PDF
Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the relationship between the prices of wheat and rice importer in Iraq and crude oil prices and the exchange rate using the ARDL model
...Show More Authors

Since the beginning of 21st century, the prices of Agricultural crops have increased. This Increases is accompanied with that increases of crude oil prices and fluctuation of a dollar exchange rate as a dominant currency used in the global trade. The paper aimed to analysis the short run and long run cointegration relationships between prices of some of Agricultural crops imported by Iraq such as wheat and rice crops and both the crude oil prices and the Iraq dinar exchange rate a gained America dollar using ARDL model. The results show the long run equilibrium between they three variable throng the error correction mechanizem. The results also show the significant and economically sound effects of cru

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Petroleum Research And Studies
Stress Ratio Method to Predict Fracture Pressure Gradient in Southern Iraqi Deep Wells
...Show More Authors

This research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica

... Show More
Publication Date
Thu May 02 2024
Journal Name
Petroleum And Coal
Wellbore Instability Analysis to Determine the Failure Criteria for Deep Well/H Oilfield
...Show More Authors

View Publication
Scopus (2)
Scopus
Publication Date
Mon Sep 30 2024
Journal Name
Medical Journal Of Babylon
Effectiveness of Deep Breathing Technique on Pain Level of School Children during Catheterization
...Show More Authors

Scopus (6)
Scopus
Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
...Show More Authors

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

... Show More
View Publication Preview PDF
Scopus (37)
Crossref (29)
Scopus Clarivate Crossref
Publication Date
Sat Feb 01 2025
Journal Name
Civil Engineering Journal
On the Impact of Lacing Reinforcement Arrangement on Reinforced Concrete Deep Beams Performance
...Show More Authors

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

... Show More
View Publication
Scopus (1)
Scopus Clarivate Crossref
Publication Date
Sat Feb 01 2025
Journal Name
Civil Engineering Journal
On the Impact of Lacing Reinforcement Arrangement on Reinforced Concrete Deep Beams Performance
...Show More Authors

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

... Show More
Scopus (1)
Scopus Clarivate Crossref
Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
...Show More Authors

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Thu Jul 13 2023
Journal Name
International Journal Of Research In Social Sciences & Humanities
Subject Review: Blogs as Learning Tools in EFL Classrooms
...Show More Authors

Blogs have emerged as a powerful technology tool for English as a Foreign Language (EFL) classrooms. This literature review aims to provide an overview of the use of blogs as learning tools in EFL classrooms. The study examines the benefits and challenges of using blogs for language learning and the different types of blogs that can be used for language learning. It provides suggestions for teachers interested in using blogs as learning tools in their EFL classrooms. The findings suggest that blogs are a valuable and effective tool for language learning, particularly in promoting collaboration, communication, and motivation.

View Publication Preview PDF
Crossref