Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Articles by Mohammed BA
A feature-enriched deep learning based ensemble framework for robust phishing URL detection
Through the prevalence of internet technologies and the integration of digitalization into our daily routine, a significant portion of our personal, financial, and professional activities has shifted to cyberspace. However, this transformation has led to the rise of cyber threats, with phishing attacks being among the most dangerous and widespread. By exploiting the open and anonymous aspects of the internet, phishing attacks target experienced and inexperienced users.
Partially adaptive optimization driven spatial focused CNN with Gompertz non-linearity for interpretable Alzheimer’s disease diagnosis
Artificial intelligence (AI) has recently demonstrated promising results in medical diagnostics. These advancements play a key role in enhanced accuracy and precision (Dave et al., 2025; Khan et al., 2025; Gencer & Gencer, 2025). The effectiveness of the treatment relies on the availability of medical data like health surveys and other reports.
Federated proximal learning with data augmentation for brain tumor classification under heterogeneous data distributions
Technological advancements in healthcare have changed medical imaging of brain tumors, enhancing early and precise disease diagnosis, which is important for proper patient treatment. Among these innovations, magnetic resonance imaging (MRI)-based imaging systems have significantly improved the detection and management of critical conditions such as brain tumors.
Enhancing emotion classification on the ISEAR dataset using fine-tuning and data augmentation with hybrid transformer models
Natural language processing (NLP) is a branch of artificial intelligence (AI) that aims to develop a mechanism for machines to use natural language. However, some NLP tasks require a language-specific approach. Emotions/sensitivity analysis is one such task in a NLP system (Ullah et al., 2024). In NLP sentiment analysis and human-computer interaction (HCI), emotion classification is essential in building applications that understand and respond to human emotions.
Enhancing privacy-preserving brain tumor classification with adaptive reputation-aware federated learning and homomorphic encryption
Brain tumors are a very critical condition, and immediate identification and treatment are required to improve patient survival rates. Diagnosis of brain tumors is often done using magnetic resonance imaging (MRI) and computed tomography (CT) scans. MRI scans are usually preferred over CT scans because they do not cause radiation exposure. Tumors can be of two types: benign and malignant.
The effect of the Buteyko breathing technique on asthma control and quality of life in children with asthma aged 7-12 years: a randomized controlled study [PeerJ]
Asthma in childhood is characterized by chronic airway inflammation. Chronic inflammation of the airways causes symptoms such as recurrent morning and nighttime cough and chest tightness in children. These inflammations are explained by airway structural cells such as T lymphocytes, smooth muscle endothelial cells and eosinophils (Global Initiative for Asthma, 2024; Türk Toraks Derneği, 2020).
Enhancing phishing detection with dynamic optimization and character-level deep learning in cloud environments
This section reviews various well-established phishing detection frameworks built upon ML and DL techniques. Prasad & Chandra (2024) developed a cyber-threat intelligence-based malicious URL recognition method has been proposed utilizing dual-stage ensemble learning. The cyber threat intelligence-based (CTI) features removed from Google explorations and Who is websites are employed to enhance the performance of recognition.
Microscopic parasite malaria classification using best feature selection based on generalized normal distribution optimization
Microscopic parasite malaria classification using best feature selection based on generalized normal distribution optimization 1University of Wah, Department of Computer Science, Wah Cantt, Pakistan 2National University of Technology (NUTECH), Islamabad, Pakistan 3Department of Information Sciences, University of Education Lahore, Jauharabad Campus, Jauharabad, Pakistan 4Noroff University College, Kristiansand, Norway 5Artificial Intelligence Research Center (AIRC), Ajman University, Ajman,...
The application of advanced computational algorithms used for cooperative communication transmission of vehicular networks: a proposed method
The basic idea of collaborative communication is based on a multiuser communication environment. A single-antenna mobile user forms a virtual multi-antenna array by sharing the antennas of multiple mobile terminals nearby, thereby gaining diversity and effectively improving the reliability of information transmission (Dias et al., 2020).
A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks
Future scope In this section, we identify the promising research directions in applying AI-based solutions, with the aim to promote and facilitate further research. Algorithms like iASEF (Dohare & Singh, 2020) should be used in the future to solve physical world issues. Furthermore, novel optimization strategies based on self-adaptive methodologies may be used to address the network’s energy issue.
Show More
loading
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Mohammed
Contact Mohammed, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack