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
There is the continuous increase in death rate related to cardiac disease across the world. Prediction of the heart disease in advance may help the experts to suggest the pre-emptive measures to minimize the death risk.…
Coronary Artery Disease (CAD) is one of the most common cardiac diseases worldwide and causes disability and economic burden. It is the world’s leading and most serious cause of mortality, with approximately 80% of death…
The past few years have observed substantial growth in death rates associated with brain tumors and it is second foremost source of cancer-related demises. However, it is possible to increase the chance of survival if tu…
The globe was rocked by unprecedented levels of disruption, which had devastating effects on daily life, global health, and global economy. Since the COVID-19 epidemic started, methods for delivering accurate diagnoses f…
Brain MRI (Magnetic Resonance Imaging) classification is one of the most significant areas of medical imaging. Among different types of procedures, MRI is the most trusted one to detect brain diseases. Manual and semi-au…
A cyberattack is a serious crime that could affect medical organizations. These attacks could affect medical organization sensitive data disclosure, loss of organization data, or the business's continuity. The Man-in-The…
Because the morbidity data of infectious diseases do not only have a single linear or nonlinear characteristic, but also have both linear and nonlinear characteristics, the combination model prediction method is often us…
The accurate analysis of medical data is dependent on early disease detection and the value of accuracy is reduced when the medical data quality is poor. However, existing techniques have lower efficiency in handling het…
Over the years, a wide variety of respiratory diseases have caused a high mortality rate throughout the world. This was again observed with the appearance of the pandemic, COVID-19. In addition, the most affected are peo…
Intelligent networking is a concept that enables 5G, the Internet of Things (IoT) and artificial intelligence (AI) to combine as a way to accelerate technological innovation and develop new revolutionary digital services…
