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
Road crash injury severity prediction is essential for intelligent transportation systems, yet challenged by severe class imbalance, rigid 4-class severity schemes (unhurt/slight/hospitalized/fatal), and optimal methodol…
Fake news detection has become a major problem in the digital age. This study presents an improved machine learning technique that achieves 91.99% accuracy in predicting fake news detection within Albanian textual datase…
Autism Spectrum Disorder (ASD) is a complex neurological developmental disability that appears during early childhood. Conventional ASD diagnostic techniques rely on behavioural observations, characteristics, and clinica…
Software project management must make high-stakes decisions under uncertainty in effort estimation, cost control, and execution risk. Although machine learning has enhanced predictive accuracy, several studies employ it…
Cardiopathy is one of the most serious diseases worldwide with its high morbidity and mortality rates posing a latent risk over time. The objective of this research focuses on evaluating Machine Learning (ML) models such…
Voice dysfunction is a common complication following thyroid surgery. However, the application of explainable machine learning for predicting postoperative voice recovery remains largely unexplored. Therefore, an investi…
The Multimodal Sentiment Analysis (MSA) land-scape for Arabic content is strikingly underexplored, mainly due to limited datasets and a lack of robust integration methods across text, audio, and image. While transformer-…
Quantum data processing requires classical data to be encoded into quantum states. Current noisy intermediate-scale quantum devices have a limited number of qubits that are stable only briefly. Encoding classical data in…
The security and protection of models in dis-tributed machine learning (ML) systems require high emphasis on adversarial threats, including poisoning attacks. This study contains a complete framework that integrates diff…
This research introduces a CPU-optimized static malware-detection framework for resource-constrained environments, such as endpoints and IoT devices. We address the significant challenge of high memory and computational…
