Waheeb Baddah, Hamzah Ali Qasem, Ayman Alsabry, Rana Saleh Al Gawani, Wafa Mohammed Alzuraiqi, FE Hanash
2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA) · 2024 · pp. 1–10
The problem of data imbalance poses a significant challenge in the field of medical diagnostics, particularly in heart disease prediction using machine learning models. This study investigates the application of the Synthetic Minority Over-sampling Technique (SMOTE) to address this imbalance…
heart disease prediction
SMOTE
Machine learning
Imbalance Datasets
Ayman Alsabry
Hamzah Ali Abdulrahman Qasem
Malek Algabri
Amin Mohamed Ahsan
Mogeeb A. A. Mosleh
F. E. Hanash
International Journal of Computing · 2024 · Vol. 2 · No. 23 · pp. 254–267
Breast cancer (BC) is a major global health concern. Detecting BC at an early stage gives more treatment options and can help avoid more aggressive treatments. The use of machine learning (ML) in BC prediction offers significant potential for improving…
Data Exploration
Ensemble Classifier
Hyperparameters Tuning
Machine Learning
Abeer Abdullah Shujaaddeen, Fadl Mutaher Ba-Alwi, Ammar T Zahary, Ahmed Sultan Alhegami, Ayman Alsabry, Abdulkader M Al-Badani
2024 1st International Conference on Emerging Technologies for Dependable Internet of Things (ICETI) · 2024 · pp. 1–9
In this paper, a model was built to compare the performance of the following machine learning (ML) models: DT, RF, SVM, and MLP, using two types of classification: binary classification and multi classification. The researchers concluded that the MLP classifier…
Binary Classification
Multivariate Classification
Multi-class Model
Machine Learning
Machine Learning Models
Machine Learning Techniques
Type Classification
Tax Authorities
Confusion Matrix
Multi-label
Multiple Classes
Fraud Detection
Tax Administration
RapidMiner
Financial Fraud
Abdulsalam Tonin, Malek Algabri, Ayman Alsabry, Ali Abdullah Mohammed Ali, Abdualmajed AG Al-Khulaidi, Mossa Ghurab
Sana’a University Journal of Applied Sciences and Technology · 2024 · Vol. 2 · No. 3 · pp. 275–292
Mobile ad-hoc networks are deployed in different fields and it can be effective in applications that depend on the inter-node interaction such as search and rescue, surveillance, and battlefield reconnaissance. Due to this importance, in this article, we have reviewed…
MANET
Evaluation Metrics
Energy Consumption Optimization
Scalability
Network’s lifetime
Stability
Performance Evaluation
Energy Efficiency
Ayman Alsabry, Malek Algabri
Informatics and Automation · 2024 · Vol. 1 · No. 23 · pp. 129–168
Abstract: The study presents a method for iterative parameter tuning of tree ensemble-based models using Bayesian hyperparameter tuning for states prediction, using breast cancer as an example. The proposed method utilizes three different datasets, including the Wisconsin Diagnostic Breast Cancer…
iterative tuning
tree ensemble-based models
bayesian optimization
breast cancer
machine learning.
Waheeb Baddah, Hamzah Ali Qasem, Ayman Alsabry, Awadh abdo Mohammed, FE Hanash
2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA) · 2023 · pp. 1–8
heart disease is a prevalent cause of mortality worldwide, and the ability to identify and prevent this ailment at an early stage is crucial for enhancing patient outcomes. Recently, researchers have focused on utilizing Machine-Learning (ML) techniques to predict risk…
Heart disease prediction
K-Nearest Neighbors Algorithm
Machine learning
Hyperparameter tuning optimization
Abdulrahman Mohammed Hussein Obaid, Awadh Ali Abdo Mohammed, Santosh K Pani, Ayman Alsabry, Hamzah Ali Qasem
2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA) · 2023 · pp. 1–12
Computing, Internet, digital devices, smart devices, and other technologies were leading to a new terminology known as cloud of things (CoT). Cloud of Things is a powerful technology used to analyze and store massive data from thousands of distributed devices…
Computing
Cloud of Things
Scheduling Algorithms
Scientific Workflow
Survey
Taxonomy
Ayman Alsabry, Malek Algabri, Amin Mohamed Ahsan, Mogeeb AA Mosleh, Aqeel Abdullah Ahmed, Hamzah Ali Qasem
2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA) · 2023 · pp. 1–8
Breast cancer (BC) is a critical public health concern, and the development of accurate prediction models is crucial for early detection. However, predicting BC using imbalanced datasets poses challenges for achieving accurate predictions. This study aims to enhance the performance…
Breast Cancer
SMOTE
Breast Cancer Coimbra Dataset
Machine learning
Ayman Alsabry, Malek Algabri, Amin Mohamed Ahsan, Mogeeb AA Mosleh, Aqeel Abdullah Ahmed, Hamzah Ali Qasem
2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA) · 2023 · pp. 1–8
Breast cancer (BC) is a major health concern affecting women worldwide, and early detection is crucial for effective treatment and improved survival rates. In this study, we propose a novel BC prediction framework based on iterative optimization with Bayesian hyperparameter…
Breast Cancer
SMOTE
Breast Bayesian hyperparameter tuning
Machine learning
Mogeeb AA Mosleh, Abdulrahman Mohammed Al-Fakaih, Ayman Mohammed Al-Najar, Basheer Abdulraqeeb Farea, Mohammed Abdu Mugahed, Ahmed Salah Aldabe, Mohammed Abdallah Al-Kebsi, Ayman AlSabry
International Conference on Electronics and Signal Processing · 2023 · pp. 25–34
Face recognition is a subfield of artificial intelligence science that uses different biometric features of human faces to recognize people. Face recognition systems are widely used due to highly achieved recognition accuracy reaching almost 99.73%. However, there are several challenges…
