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HISHAM KHALAF ALLAHEM

Assistant Professor

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allahem@ju.edu.sa
Information Systems - Computer and Information Sciences College
College
Computer and Information Sciences College
كلية علوم الحاسب والمعلومات
Department
Information Systems
نظم المعلومات
Researches
12
12
Page Visits
No view count available

Fm researches

Last Researches

AI-based prediction of traffic crash severity for improving road safety and transportation efficiency
HISHAM KHALAF ZAYED ALLAHEM
Efficient Arabic Essay Scoring with Hybrid Models: Feature Selection, Data Optimization, and Performance Trade-offs
HISHAM KHALAF ZAYED ALLAHEM
Optimized YOLOv8 for Enhanced Breast Tumor Segmentation in Ultrasound Imaging
HISHAM KHALAF ZAYED ALLAHEM

fm info

Researches

AI-based prediction of traffic crash severity for improving road safety and transportation efficiency
HISHAM KHALAF ZAYED ALLAHEM
Efficient Arabic Essay Scoring with Hybrid Models: Feature Selection, Data Optimization, and Performance Trade-offs
HISHAM KHALAF ZAYED ALLAHEM
Optimized YOLOv8 for Enhanced Breast Tumor Segmentation in Ultrasound Imaging
HISHAM KHALAF ZAYED ALLAHEM
A Hybrid Model of Feature Extraction and Dimensionality Reduction Using ViT, PCA, and Random Forest for Multi-Classification of Brain Cancer
HISHAM KHALAF ZAYED ALLAHEM
Aggregated Catalyst Physicochemical Descriptor-Driven Machine Learning for Catalyst Optimization: Insights into Oxidative-Coupling-of-Methane Dynamics and C2 Yields
HISHAM KHALAF ZAYED ALLAHEM
Innovative Tailored Semantic Embedding and Machine Learning for Precise Prediction of Drug-Drug Interaction Seriousness
HISHAM KHALAF ZAYED ALLAHEM
Comprehensive Network Analysis of Lung Cancer Biomarkers Identifying Key Genes Through RNA-Seq Data and PPI Networks
HISHAM KHALAF ZAYED ALLAHEM
Enhancing Breast Cancer Detection in Ultrasound Images: An Innovative Approach Using Progressive Fine-Tuning of Vision Transformer Models
HISHAM KHALAF ZAYED ALLAHEM
Layer-Weighted Attention and Ascending Feature Selection: An Approach for Seriousness Level Prediction Using the FDA Adverse Event Reporting System
HISHAM KHALAF ZAYED ALLAHEM
Automated labour detection framework to monitor pregnant women with a high risk of premature labour using machine learning and deep learning
HISHAM KHALAF ZAYED ALLAHEM
Automated uterine contractions pattern detection framework to monitor pregnant women with a high risk of premature labour
HISHAM KHALAF ZAYED ALLAHEM
Framework to monitor pregnant women with a high risk of premature labour using sensor networks
HISHAM KHALAF ZAYED ALLAHEM
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