334 citations · 1.9k across the 45 of their papers we have counts for
51 papers
Semi-Supervised Learning-Based Genetic Biomarkers Dataset for Multiple-Stage Hepatocellular Carcinoma Prediction
Ahmed Ammar Kubba, Manar Abu Talib, Jibran Sualeh Muhammad +4
Liver cancer is a complex disease responsible for a high number of deaths across the globe each year, making automated solutions for liver cancer classification urgent. The most co…
Potential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer
Ali Bou Nassif, Darko Castven, Manar Abu Talib +4
This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective biomarkers across five differen…
Optimization Algorithms in Smart Grids: A Systematic Literature Review
Sidra Aslam, Ala Altaweel, Ali Bou Nassif
Electrical smart grids are units that supply electricity from power plants to the users to yield reduced costs, power failures/loss, and maximized energy management. Smart grids (S…
What UAE Software Students Think about Software Testing: A Replicated Study
Luiz Fernando Capretz, Saad Harous, Ali Bou Nassif
Software testing is vital to improve software quality. However, software tester role is stigmatized, partly due to misperception and partly due to the treatment of the testing proc…
On the Value of Project Productivity for Early Effort Estimation
Mohammad Azzeh, Ali Bou Nassif, Yousef Elsheikh +1
In general, estimating software effort using a Use Case Point (UCP) size requires the use of productivity as a second prediction factor. However, there are three drawbacks to this…
Arabic Fake News Detection Based on Deep Contextualized Embedding Models
Ali Bou Nassif, Ashraf Elnagar, Omar Elgendy +1
Social media is becoming a source of news for many people due to its ease and freedom of use. As a result, fake news has been spreading quickly and easily regardless of its credibi…
Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet
Omar Mahdi, Ali Bou Nassif
In this work, we introduce a spatially transformed DenseNet architecture for transformation invariant classification of cancer tissue. Our architecture increases the accuracy of th…
Breast cancer detection using artificial intelligence techniques: A systematic literature review
Ali Bou Nassif, Manar Abu Talib, Qassim Nasir +2
Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has been developed for it. Breast cancer is one of the most common cancer types. According to the…
Emotional Speaker Identification using a Novel Capsule Nets Model
Ali Bou Nassif, Ismail Shahin, Ashraf Elnagar +3
Speaker recognition systems are widely used in various applications to identify a person by their voice; however, the high degree of variability in speech signals makes this a chal…
Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review
Ali Bou Nassif, Bassel Soudan, Mohammad Azzeh +2
Electrical utilities depend on short-term demand forecasting to proactively adjust production and distribution in anticipation of major variations. This systematic review analyzes…
Novel Hybrid DNN Approaches for Speaker Verification in Emotional and Stressful Talking Environments
Ismail Shahin, Ali Bou Nassif, Nawel Nemmour +3
In this work, we conducted an empirical comparative study of the performance of text-independent speaker verification in emotional and stressful environments. This work combined de…
Novel Dual-Channel Long Short-Term Memory Compressed Capsule Networks for Emotion Recognition
Ismail Shahin, Noor Hindawi, Ali Bou Nassif +2
Recent analysis on speech emotion recognition has made considerable advances with the use of MFCCs spectrogram features and the implementation of neural network approaches such as…
COVID-19 Electrocardiograms Classification using CNN Models
Ismail Shahin, Ali Bou Nassif, Mohamed Bader Alsabek
With the periodic rise and fall of COVID-19 and numerous countries being affected by its ramifications, there has been a tremendous amount of work that has been done by scientists,…
The exploitation of Multiple Feature Extraction Techniques for Speaker Identification in Emotional States under Disguised Voices
Noor Ahmad Al Hindawi, Ismail Shahin, Ali Bou Nassif
Due to improvements in artificial intelligence, speaker identification (SI) technologies have brought a great direction and are now widely used in a variety of sectors. One of the…
Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis
Ali Bou Nassif, Abdollah Masoud Darya, Ashraf Elnagar
This work presents a detailed comparison of the performance of deep learning models such as convolutional neural networks (CNN), long short-term memory (LSTM), gated recurrent unit…
The empirical study of e-learning post-acceptance after the spread of COVID-19: A multi-analytical approach based hybrid SEM-ANN
Ashraf Elnagar, Imad Afyouni, Ismail Shahin +2
There are several reasons why the fear of vaccination has caused population rejection. Questions have been raised by students regarding the effectiveness of vaccines, which in turn…
Reliability Models for Smartphone Applications
Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz
Smartphones have become the most used electronic devices. They carry out most of the functionalities of desktops, offering various useful applications that suit the users needs. Th…
Empirical Analysis on Productivity Prediction and Locality for Use Case Points Method
Mohammad Azzeh, Ali Bou Nassif, Cuauhtemoc Lopez Martin
Use Case Points (UCP) method has been around for over two decades. Although, there was a substantial criticism concerning the algebraic construction and factors assessment of UCP,…
CASA-Based Speaker Identification Using Cascaded GMM-CNN Classifier in Noisy and Emotional Talking Conditions
Ali Bou Nassif, Ismail Shahin, Shibani Hamsa +2
This work aims at intensifying text-independent speaker identification performance in real application situations such as noisy and emotional talking conditions. This is achieved b…
Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif +1
The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. Howev…
Predicting Software Effort from Use Case Points: A Systematic Review
Mohammad Azzeh, Ali Bou Nassif, Imtinan Attili
Context: Predicting software project effort from Use Case Points (UCP) method is increasingly used among researchers and practitioners. However, unlike other effort estimation doma…
Multi-Stage Optimized Machine Learning Framework for Network Intrusion Detection
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif +1
Cyber-security garnered significant attention due to the increased dependency of individuals and organizations on the Internet and their concern about the security and privacy of t…
Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detection
MohammadNoor Injadat, Fadi Salo, Ali Bou Nassif +2
Network attacks have been very prevalent as their rate is growing tremendously. Both organization and individuals are now concerned about their confidentiality, integrity and avail…
Multi-split Optimized Bagging Ensemble Model Selection for Multi-class Educational Data Mining
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif +1
Predicting students' academic performance has been a research area of interest in recent years with many institutions focusing on improving the students' performance and the educat…