A5103214435- Radiation Shielding Materials Analysis
- Glass properties and applications
- Nuclear materials and radiation effects
- Advanced X-ray and CT Imaging
- Radioactivity and Radon Measurements
- Radiation Dose and Imaging
- Luminescence Properties of Advanced Materials
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Geochemistry and Geologic Mapping
- AI in cancer detection
- Multiple Sclerosis Research Studies
- Advanced Radiotherapy Techniques
- Polymer Nanocomposite Synthesis and Irradiation
- Graphite, nuclear technology, radiation studies
- Nanofluid Flow and Heat Transfer
- Estrogen and related hormone effects
- Health and Well-being Studies
- Acute Ischemic Stroke Management
- Bone Tissue Engineering Materials
- Heat Transfer Mechanisms
- Graphene and Nanomaterials Applications
- Genetic factors in colorectal cancer
- Brain Tumor Detection and Classification
King Khalid University
2016-2025
University of Leicester
2015-2025
King Faisal Specialist Hospital & Research Centre
2024-2025
Armed Forces Hospital
2019-2025
King Saud bin Abdulaziz University for Health Sciences
2018-2025
Riyadh Armed Forces Hospital
2025
King Saud University
2018-2024
Texas A&M International University
2023-2024
Prince Sattam Bin Abdulaziz University
2020-2024
King Abdulaziz Medical City
2018-2024
Accurate radiogenomic classification of brain tumors is important to improve the standard diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused radiomic predicting genetic subtype A fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, proposed feature extraction fuses quantitative...
The current exploration focuses on the impact of homogeneous and heterogeneous chemical reactions titanium dioxide-ethylene glycol (EG)-based nanoliquid flow over a rotating disk with thermal radiation. In this paper, horizontal uniform magnetic field is used to regularise produced by disk. Further, we conduct comparative study fluid without aggregation. Suitable transformations are convert governing partial differential equations (PDEs) into ordinary (ODEs). Later, attained system solved...
A new nano-silica/chitosan (SiO2/CS) sorbent was created using a wet process to eliminate uranium(VI) from its solution. Measurements BET, XRD, EDX, SEM, and FTIR were utilized analyze the production of SiO2/CS. The adsorption progressions carried out by pH, SiO2/CS dose, temperature, sorbing time, U(VI) concentration measurements. optimal condition for sorption (165 mg/g) found be pH 3.5, 60 mg SiO2/CS, 50 min 200 mg/L U(VI). Both second-order kinetics Langmuir model observed obeyed ability...
In this present work, a PVA/PVP-blend polymer was doped with various concentrations of neodymium oxide (PB-Nd+3) composite films using the solution casting technique. X-ray diffraction (XRD) analysis used to investigate structure and proved semi-crystallinity pure PVA/PVP polymeric sample. Furthermore, Fourier transform infrared (FT-IR) analysis, chemical-structure tool, illustrated significant interaction PB-Nd+3 elements in blends. The transmittance data reached 88% for host blend matrix,...
The Brain Tumor presents a highly critical situation concerning the brain, characterized by uncontrolled growth of an abnormal cell cluster. Early brain tumor detection is essential for accurate diagnosis and effective treatment planning. In this paper, novel Convolutional Neural Network (CNN) based Graph (GNN) model proposed using publicly available dataset from Kaggle to predict whether person has or not if yes then which type (Meningioma, Pituitary Glioma). objective research models...
One of the most difficult challenges in medicine is predicting heart disease at an early stage. In this study, six machine learning (ML) algorithms, viz., logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest classifier, and extreme gradient boosting, were used to analyze two datasets. dataset was UCI Kaggle Cleveland other comprehensive Cleveland, Hungary, Switzerland, Long Beach V. The performance results techniques obtained. with tuned...
ZnO-doped Polyvinyl alcohol/polyvinyl pyrrolidone (PVA/PVP) polymeric films were prepared in this study through an easy and inexpensive solution-casting method. The scope of the was based on structural, dielectric, optical parameters, as well limiting effects polymer blend (PB) nanocomposite films. X-ray diffraction (XRD) analysis indicated that synthesized nanocomposites semicrystalline. calculated crystalline size semicrystalline peak decreased ZnO increased or enhanced polymer. Fourier’s...
A new synthetic material, namely, (3-(((4-((5-(((S)-hydroxyhydrophosphoryl)oxy)-2-nitrobenzylidene) amino) phenyl) imino) methyl)-4-nitrophenyl hydrogen (R)-phosphonate)), was subjected to a quaternary ammonium salt and named (HNAP/QA). Several characterizations, such as FTIR spectrometry, 1H-NMR analysis, 13C-NMR 31P-NMR Analysis, TGA GC-MS were performed ensure its felicitous preparation. HNAP/QA is capable of the selective adsorption W(VI) ions from solutions rock leachate. The optimum...
Abstract The present research aims to predict effluent soluble chemical oxygen demand (SCOD) in anaerobic digestion (AD) process using machine-learning based approach. Anaerobic is a highly sensitive and depends upon several environmental operational factors, such as temperature, flow, load. Therefore, predicting output characteristics modeling important not only for monitoring control, but also reduce the operating cost of treatment plant. It difficult COD real time mode, so it better use...
Abstract Breast Cancer is a significant global health challenge, particularly affecting women with higher mortality compared other cancer types. Timely detection of such types crucial, and recent research, employing deep learning techniques, shows promise in earlier detection. The research focuses on the early tumors using mammogram images deep-learning models. paper utilized four public databases where similar amount 986 mammograms each for three classes (normal, benign, malignant) are...