The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on machine learning — spanning algorithms, applications, and techniques across computer science domains. One of the journal's largest and most active research areas.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
Imbalanced datasets pose significant challenges in healthcare for developing accurate predictive models in medical diagnostics. In this work, we explore the effectiveness of combining resampling methods with machine lear…
Plant diseases pose a significant challenge to agriculture, leading to serious economic losses and a risk to food security. Predicting and managing diseases such as potato blight requires an analysis of key environmental…
In the modern era of cyber security, cyber-attacks are continuously evolving in terms of complexity and frequency. In this context, organizations need to enhance Network Intrusion Detection Systems (NIDS) for anomaly det…
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IJACSA`s Publication Principles. We hereby retract the content of t…
Sentiment Analysis (SA) effectively examines big data, such as customer reviews, market research, social media posts, online discussions, and customer feedback evaluation. Arabic Language is a complex and rich language.…
Monte Carlo (MC) rendering is a powerful technique for achieving photorealistic images by simulating complex light interactions. However, the inherent noise introduced by MC rendering necessitates effective denoising tec…
Effective resource estimation is essential in cloud computing to minimize operational costs, optimize performance, and enhance user satisfaction. This study proposes a comprehensive framework for virtual machine optimiza…
Despite advancements in machine learning within healthcare, the majority of predictive models for ICU mortality lack interpretability, a crucial factor for clinical application. The complexity inherent in high-dimensiona…
The natural language processing paradigm has emerged as a vital tool for addressing complex business challenges, mainly due to advancements in machine learning (ML), deep learning (DL), and Generative AI. Advanced NLP mo…
Early detection and precise prediction are essential in medical diagnosis, particularly for diseases such as diabetic nephropathy (DN), which tends to go undiagnosed at its early stages. Conventional diagnostic technique…
