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Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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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.

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Publication Date
Fri Feb 13 2026
Journal Name
Journal Of Physical Education
The Effect of Varied Teaching Strategies on Learning Backstroke Swimming for Students
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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering & Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Unsupervised Learning: Discovering Patterns without Labels: Health Care, E-Commerce, and Cybersecurity
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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The Philosophy of Organizational Forgetting In Frame of Learning and Organizational knowledge
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current research aims to build an intellectual framework for concept of organizational forgetting, which is considered one of the most important topics in contemporary management thought, which is gain the consideration of most scholars and researchers in field of organizational behavior, which is to be a loss of intentional or unintentional knowledge of any organizational level. It turned out that just as organizations should learn and acquire knowledge, they must also forget, especially knowledge obsolete and worn out. And represented the research problem in the absence of Arab research dealing with organizational forgetting, and highlights the supporting infrastructure core, and show a close relationship with organizational le

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Thu May 06 2021
Journal Name
Tesol International Journal
The Effect of Types of Blended Learning Strategies on EFL Students` Achievements
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This work aims at finding out the impact of teaching types blended learning strategies on academic students` achievement. A review of related literature indicates that almost no study has ever attempted to focus specifically on the effect of the different kinds of blended learning strategies on EFL students` achievement in the educational research writing, and the present study attempts to fill this gap. The study focused on the students at the Master's degree in Educational Research Writing in the first semester of the academic year 2020/2021. The sample has selected from the college of Education Ibn-Rushd (18) students. Material has been designed for the Master candidates’ participants of the study was divided into two groups: one an e

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Sun Jan 01 2023
Journal Name
Corporate And Business Strategy Review
The role of learning organizations in crisis management strategy: A case study
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The problem of the paper focused on the role of the learning organization in the crisis management strategy, and the extent of the actual interest in both the learning organization and the crisis management and aimed at diagnosing and analyzing that and surrounding questions. The Statistical Package for the Social Sciences (SPSS) program was used to calculate the results and the correlation coefficient between the two main variables. The methodology was descriptive and analytical. The case study was followed by a questionnaire that was distributed to a sample of 31 teachers. The paper adopted a seven-dimensional model of systemic thinking that encourages questioning, empowerment, provision of advanced technologies, and strategic lea

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Publication Date
Sun Sep 26 2021
Journal Name
Modern Sport
The Effect Of Plank Exercises On The Lipid Component And The Rate Of Metabolism (Bmr) Among Students Of The Higher Institute For Security And Administrative Development
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The introduction of the research on the science of training and the physiology of sports was addressed from important sciences, where the physical effort drew the attention of scientists since the past centuries when they studied how the body performs its functions when performing physical exertion and observe the changes that occur in it and write down and study especially the positive effects of the practice of daily sports The aim of the study was to investigate the effect of plank exercises on the lipid component and the metabolic rate (bmr) of the female students of the Higher Institute for Security and Management Development. As for the third chapter, the two researchers used the experimental method on a sample of the female s

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