Hassan A. Alshamrani
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View article: Integration of corpus linguistics and deep learning techniques for enhanced semantic-driven emotion detection on textual data
Integration of corpus linguistics and deep learning techniques for enhanced semantic-driven emotion detection on textual data Open
Corpus linguistics provides an organized framework for examining a massive set of texts (corpora) to reveal structures, patterns, and interpretations in the language. Under the field of text-based emotion recognition (TER), corpus linguist…
View article: Maternal Diabetes Mellitus and Neonatal Outcomes in Bisha: A Retrospective Cohort Study
Maternal Diabetes Mellitus and Neonatal Outcomes in Bisha: A Retrospective Cohort Study Open
Background: Maternal diabetes mellitus (MDM) is associated with increased risks for adverse neonatal outcomes. However, the impact of MDM on neonatal outcomes in Bisha, a city in Saudi Arabia, is not well documented. This study aims to inv…
View article: Health Problems and Disabilities Among the Postmenopausal Saudi Women in Bisha City Receiving Home Care: A Descriptive Cross-Sectional Study
Health Problems and Disabilities Among the Postmenopausal Saudi Women in Bisha City Receiving Home Care: A Descriptive Cross-Sectional Study Open
Postmenopausal women in Bisha city who receive home care services experience a range of health problems and disabilities, particularly related to hypertension, diabetes, and musculoskeletal disorders. The findings of this study can help he…
View article: Maternal Diabetes Mellitus and Neonatal Outcomes in Bisha: A Retrospective Cohort Study.
Maternal Diabetes Mellitus and Neonatal Outcomes in Bisha: A Retrospective Cohort Study. Open
Background: Maternal diabetes mellitus (MDM) is associated with increased risks for adverse neonatal outcomes. However, the impact of MDM on neonatal outcomes in Bisha, a city in Saudi Arabia, is not well-documented. This study aims to inv…
View article: Generative and Discriminative Learning for Lung X-Ray Analysis Based on Probabilistic Component Analysis
Generative and Discriminative Learning for Lung X-Ray Analysis Based on Probabilistic Component Analysis Open
The method is found to achieve superior accuracy, offering a viable solution to the class of problems presented. Accuracy rates achieved by the kernels in the NN and SVM models were 95.02% and 92.45%, respectively, suggesting the method's …
View article: A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images
A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images Open
BACKGROUND: By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value…
View article: Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach
Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach Open
Knee osteoarthritis is a challenging problem affecting many adults around the world. There are currently no medications that cure knee osteoarthritis. The only way to control the progression of knee osteoarthritis is early detection. Curre…
View article: Modified Seagull Optimization With Deep Learning for Affect Classification in Arabic Tweets
Modified Seagull Optimization With Deep Learning for Affect Classification in Arabic Tweets Open
Arabic is one of the world’s most widely spoken languages, and there is a huge amount of digital content available in Arabic. By the categorization of Arabic documents, it becomes easier to search and access specific content of interest. W…
View article: Enhanced Adaptive Brain-Computer Interface Approach for Intelligent Assistance to Disabled Peoples
Enhanced Adaptive Brain-Computer Interface Approach for Intelligent Assistance to Disabled Peoples Open
Assistive devices for disabled people with the help of Brain-Computer Interaction (BCI) technology are becoming vital bio-medical engineering. People with physical disabilities need some assistive devices to perform their daily tasks. In t…
View article: Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data
Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data Open
Gender analysis of Twitter could reveal significant socio-cultural differences between female and male users. Efforts had been made to analyze and automatically infer gender formerly for more commonly spoken languages’ content, but, as we …
View article: Enhancement of Mammographic Images Using Histogram-Based Techniques for Their Classification Using CNN
Enhancement of Mammographic Images Using Histogram-Based Techniques for Their Classification Using CNN Open
In the world, one in eight women will develop breast cancer. Men can also develop it, but less frequently. This condition starts with uncontrolled cell division brought on by a change in the genes that regulate cell division and growth, wh…
View article: Diagnostic Validity and Reliability of Low-Dose Prospective ECG-Triggering Cardiac CT in Preoperative Assessment of Complex Congenital Heart Diseases (CHDs)
Diagnostic Validity and Reliability of Low-Dose Prospective ECG-Triggering Cardiac CT in Preoperative Assessment of Complex Congenital Heart Diseases (CHDs) Open
For the precise preoperative evaluation of complex congenital heart diseases (CHDs) with reduced radiation dose exposure, we assessed the diagnostic validity and reliability of low-dose prospective ECG-gated cardiac CT (CCT). Forty-two ind…
View article: Machine Learning-Based Models for Magnetic Resonance Imaging (MRI)-Based Brain Tumor Classification
Machine Learning-Based Models for Magnetic Resonance Imaging (MRI)-Based Brain Tumor Classification Open
In the medical profession, recent technological advancements play an essential role in the early detection and categorization of many diseases that cause mortality. The technique rising on daily basis for detecting illness in magnetic reso…
View article: Multi-Level Deep Generative Adversarial Networks for Brain Tumor Classification on Magnetic Resonance Images
Multi-Level Deep Generative Adversarial Networks for Brain Tumor Classification on Magnetic Resonance Images Open
The brain tumor is an abnormal and hysterical growth of brain tissues, and the leading cause of death affected patients worldwide. Even in this technology-based arena, brain tumor images with proper labeling and acquisition still have a pr…
View article: Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images
Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images Open
The teeth are the most challenging material to work with in the human body. Existing methods for detecting teeth problems are characterised by low efficiency, the complexity of the experiential operation, and a higher level of user interve…
View article: A U-Net-Based CNN Model for Detection and Segmentation of Brain Tumor
A U-Net-Based CNN Model for Detection and Segmentation of Brain Tumor Open
Human brain consists of millions of cells to control the overall structure of the human body. When these cells start behaving abnormally, then brain tumors occurred. Precise and initial stage brain tumor detection has always been an issue …
View article: Liver Ailment Prediction Using Random Forest Model
Liver Ailment Prediction Using Random Forest Model Open
Today, liver disease, or any deterioration in one’s ability to survive, is extremely common all around the world. Previous research has indicated that liver disease is more frequent in younger people than in older ones. When the liver’s ca…
View article: Isolated Convolutional-Neural-Network-Based Deep-Feature Extraction for Brain Tumor Classification Using Shallow Classifier
Isolated Convolutional-Neural-Network-Based Deep-Feature Extraction for Brain Tumor Classification Using Shallow Classifier Open
In today’s world, a brain tumor is one of the most serious diseases. If it is detected at an advanced stage, it might lead to a very limited survival rate. Therefore, brain tumor classification is crucial for appropriate therapeutic planni…
View article: Robust Gaussian and Nonlinear Hybrid Invariant Clustered Features Aided Approach for Speeded Brain Tumor Diagnosis
Robust Gaussian and Nonlinear Hybrid Invariant Clustered Features Aided Approach for Speeded Brain Tumor Diagnosis Open
Brain tumors reduce life expectancy due to the lack of a cure. Moreover, their diagnosis involves complex and costly procedures such as magnetic resonance imaging (MRI) and lengthy, careful examination to determine their severity. However,…
View article: The reliability of Demirjian method when determining dental age in children from Saudi Arabia
The reliability of Demirjian method when determining dental age in children from Saudi Arabia Open
The reliability of Demirjian method when determining dental age in children from
View article: A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI
A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI Open
Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to death. Magnetic resonance imaging methods capture skull images that contain healthy and affected tissue. Radiologists checked the affected tiss…
View article: Human Emotions Classification Using EEG via Audiovisual Stimuli and AI
Human Emotions Classification Using EEG via Audiovisual Stimuli and AI Open
Electroencephalogram (EEG) is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain, measured and recorded chronologically the surface of the scalp from the brain. The recorded signals fro…
View article: Breast Cancer Detection in Saudi Arabian Women Using Hybrid Machine Learning on Mammographic Images
Breast Cancer Detection in Saudi Arabian Women Using Hybrid Machine Learning on Mammographic Images Open
Breast cancer (BC) is the most common cause of women’s deaths worldwide. The mammography technique is the most important modality for the detection of BC. To detect abnormalities in mammographic images, the Breast Imaging Reporting and Dat…
View article: [Retracted] The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric
[Retracted] The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric Open
Pneumonia is a common lung disease that is the leading cause of death worldwide. It primarily affects children, accounting for 18% of all deaths in children under the age of five, the elderly, and patients with other diseases. There is a v…
View article: LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis
LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis Open
Since reporting cases of breast cancer are on the rise all over the world. Especially in regions such as Pakistan, Saudi Arabia, and the United States. Efficient methods for the early detection and diagnosis of breast cancer are needed. Th…
View article: A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images
A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images Open
Abnormal growth of brain tissues is the real cause of brain tumor. Strategy for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a patient. The manual segmentation of brain tumor magnetic resonan…
View article: Block-Wise Neural Network for Brain Tumor Identification in Magnetic Resonance Images
Block-Wise Neural Network for Brain Tumor Identification in Magnetic Resonance Images Open
The precise brain tumor diagnosis is critical and shows a vital role in the medical support for treating tumor patients. Manual brain tumor segmentation for cancer analysis from many Magnetic Resonance Images (MRIs) created in medical prac…
View article: Prevalence of urinary tract infection in children in the kingdom of Saudi Arabia
Prevalence of urinary tract infection in children in the kingdom of Saudi Arabia Open
Introduction: Urinary tract infection (UTI) is a common disorder in childhood. Early identification and appropriate antibiotic use are essential to avoid long-term sequels. The trial objective was to identify the prevalence of URI in child…
View article: PREVALENCE OF URINARY TRACT INFECTION IN CHILDREN IN THE KINGDOM OF SAUDI ARABIA
PREVALENCE OF URINARY TRACT INFECTION IN CHILDREN IN THE KINGDOM OF SAUDI ARABIA Open
Urinary tract infection (UTI) is a common disorder in childhood. Early identification and appropriate antibiotic use are essential to avoid long-term sequels. The trial objective is to identify the prevalence of URI in children, and the ri…