Neuro-symbolic AI is changing how database systems work by combining neural networks' ability to recognize patterns in data with the logical reasoning of symbolic AI. This review looks at how these two approaches work together to improve database systems in areas like query proce...
Open access
Research Article10.9734/ajrcos/2025/v18i12787
Uchenna Jeremiah Nzenwata, Goodness Oluwamayokun Opateye, Noze-Otote Aisosa, Christiana Jumoke Daramola, Oduware Collins Odigie, Emokiniovo Edwin, Inyinsisaziba Clever Ikisikpo, Oluwaferanmi Marvelous Fayemi, Sotunde Olatubosun, Keziah Oluwaseunfunmi Owolabi & Chucks Great Barry·Asian Journal of Research in Computer Science·2025
Problem Statement: Autonomous database systems represent a significant change in the management of databases, utilizing Machine Learning (ML) and Artificial Intelligence (AI) in order to carry out self-healing and self-tuning with minimal human intervention. Objectives: This syst...
Open access
Research Article10.9734/ajrcos/2025/v18i7721
Uchenna Jeremiah Nzenwata, Oluwatayofunmi Favour Durodola, Jacinta Odion Ogbeideidialu, Abiodun Elizabeth Enilolobo-Taiwo, Moyinoluwalogo Oluwatoyosi Ajayi, Tolulope Oluwadunsin Fagbohun, Muslimot Yetunde Yisau, Mayowa Emmanuel Adesuyan, Toluwalase David Oyediji & Mubarak Adetunji Adetoro·Asian Journal of Research in Computer Science·2025
Aims: This systematic review aims to explore how artificial intelligence (AI) enhances privacy-preserving techniques in database systems, focusing on anonymization, differential privacy, and secure multi-party computation (SMPC), while evaluating their effectiveness in balancing...
Open access
Research Article10.9734/ajrcos/2025/v18i7718
Machine learning (ML) and deep learning (DL) approaches have shown increasing promise for heart disease prediction, but comprehensive evidence regarding their effectiveness compared to traditional clinical methods, implementation challenges, and real-world deployment readiness re...
Open access
Research Article10.9734/ajrcos/2025/v18i12799