The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Artificial intelligence and machine learning in healthcare apply computational methods to clinical and biomedical data to support diagnosis, treatment planning, and health system operations. Common applications include medical image analysis using convolutional neural networks to detect tumors, fractures, and other abnormalities in radiology and pathology images; predictive models that estimate patient risk for readmission, sepsis, or disease progression from electronic health records; natural language processing for extracting information from clinical notes; and drug discovery models that predict molecular properties and candidate compounds. Regulatory activity reflects this growth: the FDA had authorized more than 1,300 AI-enabled medical devices by December 2025, with a record 295 cleared that year alone. Deploying AI in clinical settings raises distinct requirements around model interpretability for clinician trust, validation across diverse patient populations, and integration with existing hospital information systems. As an open-access healthcare AI journal, IJACSA publishes research on AI and machine learning models in healthcare, their clinical validation, and applied systems for diagnostic support and patient monitoring.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Recently; medical image mining has become one of the well-recognized research area(s) of machine learning and artificial intelligence techniques have been vastly used in various computer added diagnostic systems. Specifi…
The massively ever increasing amount of textual and linked biomedical data available online poses many challenges for information seekers. So, the focus of information retrieval community has shifted to precise informati…
Detection of glaucoma eye disease is still a challenging task for computer-aided diagnostics (CADx) systems. During eye screening process, the ophthalmologists measures the glaucoma by structure changes in optic disc (OD…
Debate on big data analytics has earned a remarkable interest in industry as well as academia due to knowledge, information and wisdom extraction from big data. Big data and cloud computing are two most important trends…
NGS (Next Generation Sequencing) technology has resulted in huge amount of proteomics data that exists in the form of interactions (protein-protein, gene-protein, and gene-disease). ETL (Extraction, Transformation, and L…
To precisely identify gene associated diseases has been an open area of research for biological scientists to ensure clinical and psychological symptoms and treatment for human diseases. Because whole Human Genome is def…
The United States (US) healthcare organizations are continuously struggling to cope-up with evolving regulatory requirements e.g. Health Information Technology for Economic and Clinical Health Act (HITECH) and Internatio…
Health monitoring system is an active application in pervasive and ubiquitous computing. It is an application of mobile computing technology for enhancing communication among health care workers, physicians and patients…
Discovering drug-drug interactions (DDIs) is a crucial issue for both patient safety and health care cost control. Developing text mining techniques for identifying DDIs has attracted a great deal of attention in the las…
Cluster sampling algorithm is a scheme for sequential data assimilation developed to handle general non-Gaussian and nonlinear settings. The cluster sampling algorithm can be used to solve a wide spectrum of problems tha…
