A5073823837- Online Learning and Analytics
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence in Healthcare
- FinTech, Crowdfunding, Digital Finance
- Technology-Enhanced Education Studies
- Educational Games and Gamification
- ICT in Developing Communities
- Machine Learning and Algorithms
- Information Systems Education and Curriculum Development
- Handwritten Text Recognition Techniques
- Higher Education Governance and Development
- COVID-19 diagnosis using AI
- Advanced Image and Video Retrieval Techniques
- Information Retrieval and Search Behavior
- AI in cancer detection
- Technology Adoption and User Behaviour
- Recommender Systems and Techniques
- Advanced Computational Techniques and Applications
- Ethics and Social Impacts of AI
- Stock Market Forecasting Methods
- Teaching and Learning Programming
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Network Packet Processing and Optimization
University of Leicester
2022-2024
Walter Sisulu University
2021-2023
University of the Witwatersrand
2018-2021
Elizade University
2015-2016
The emergence of artificial intelligence (AI) as a subject to be incorporated into K-12 educational levels places new demand on relevant stakeholders, especially teachers that drive the teaching and learning process. It is therefore important understand how ready are teach emerging success AI education would probably closely dependent readiness teachers. As result, this study presents an insight factors influencing behavioural intention Nigerian in-service intelligence. A total 368 teachers,...
Recent advancements in electronic commerce and communication systems have significantly increased the use of credit cards for both online regular transactions. However, there has been a steady rise fraudulent card transactions, costing financial companies huge losses every year. The development effective fraud detection algorithms is vital minimizing these losses, but it challenging because most datasets are highly imbalanced. Also, using conventional machine learning inefficient due to...
Hepatitis B is a potentially deadly liver infection caused by the hepatitis virus. It serious public health problem globally. Substantial efforts have been made to apply machine learning in detecting However, application of model interpretability limited existing literature. Model makes it easier for humans understand and trust machine-learning model. Therefore, this study, we used SHapley Additive exPlanations (SHAP), game-based theoretical approach explain visualize predictions models...
Diabetic ketoacidosis (DKA) is a serious complication that affects millions of individuals globally and presents significant health complications. Hyperchloremia, an electrolyte imbalance characterized by high levels chloride in the blood, may result gastrointestinal problems, kidney damage, even death, especially DKA patients. Early detection treatment hyperchloremia are utmost importance management DKA. This study explores potential bootstrap aggregating ensemble with random subspaces...
The integration of artificial intelligence (AI) as a subject into K-12 education worldwide is still in its early stages and undoubtedly needs further investigation. There limited effort on understanding policymakers, teachers students' viewpoints AI learning within the school system. This study gathered thoughts key stakeholders, including higher teachers, students Nigeria, to understand their conceptions, concerns, dispositions, with aim aiding implementation schools. We explored diverse...
Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. At core of this transformation is deep (DL), a subset ML that robust in processing analyzing complex large datasets. This paper provides comprehensive overview key models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Deep Belief (DBNs), Transformers, Generative Adversarial (GANs),...
The Covid-19 pandemic has affected hundreds of million lives and taken over four to date. As a result, governments policymakers see the need for emergency action reduce spread virus. In an attempt contain virus, worldwide introduced different range protection measures interventions change their citizen's behaviours, primarily through social distancing, interprovince lockdown, stay at home strategies, quarantines. lockdown have created unique challenging conditions with no documented...
Gender difference in how technology is used has been a long-time concern education. This study examined the impact of rapid transition from face-to-face learning to remote (RL) for students selected higher education institutions South Africa. The employed quantitative census sampling method as an electronic questionnaire administered 243 respondents, mainly enrolled accounting and finance department their second, third, fourth year study. In designing questionnaire, ten items Technology...
Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. At core of this transformation is deep (DL), a subset ML that robust at processing analyzing complex large datasets. This paper provides concise overview key models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Deep Belief (DBNs), Transformers, Generative Adversarial (GANs), Reinforcement...
As machine learning and data science applications grow ever more prevalent, there is an increased focus on sharing open initiatives, particularly in the context of African continent. Many argue that can support research policy design to alleviate poverty, inequality, derivative effects Africa. Despite fact datasets question are often extracted from communities, conversations around challenges accessing too driven by nonAfrican stakeholders. These perspectives frequently employ a deficit...
Xenophobia is a pressing issue in South Africa, with frequent instances of violence against immigrants. With the rise social media, platforms like Twitter reflect public sentiment on this matter. This study examines tweets from 2017 to 2022 about xenophobia using NLP, analysis, and machine learning understand feelings predict potential xenophobic incidents. The findings aim help policymakers devise strategies enhance cohesion promote more inclusive society.
Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical decisions more transparent, trustworthy, and ethically compliant. Despite its promise, sector faces several challenges, including balancing interpretability accuracy, integrating XAI into clinical workflows, ensuring adherence rigorous regulatory standards. This paper provides a comprehensive review of in healthcare, covering techniques, opportunities, advancements, thereby enhancing understanding...
The volume of information being created, generated and stored is huge. Without adequate knowledge Information Retrieval (IR) methods, the retrieval process for would be cumbersome frustrating. Studies have further revealed that IR methods are essential in centres (for example, Digital Library environment) storage information. Therefore, with more than one billion people accessing Internet, millions queries issued on a daily basis, modern Web search engines facing problem daunting scale. main...
Information and Communication Technology (ICT) is gaining ground in all areas of life, and, developing countries are taking advantage this phenomenon numerous sectors including, socio-economic development, education healthcare. With particular emphasis on healthcare, where access to appropriate information can minimize visits physicians periods hospitalization for patients suffering from chronic conditions that cause untimely death if not properly treated, e.g. asthma, diabetes, TB HIV/AIDS...
When using Information Retrieval (IR) systems, users often present search queries made of ad-hoc keywords. It is then up to the information retrieval systems (IRS) obtain a precise representation user's need and context (preferences) information. To address this problem, we investigate optimization IRS individual needs in order relevance. The goal article develop algorithms that optimize ranking documents retrieved from according user context. In particular, task led engage...