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
with the rapid improvement of computation facilities, healthcare still suffers limited storage space and lacks full utilization of computer infrastructure. That not only adds to the cost burden but also limits the possib…
Applying security to the transmitted medical images is important to protect the privacy of patients. Secure transmission requires cryptography, and watermarking to achieve confidentiality, and data integrity. Improving c…
First aid and immediate help are very important following an accident. The earlier the detection and treatment is carried out, the better the prognosis and chance of recovery of the patients. It is even more important wh…
Nowadays, many applications have been appeared due to the rapid development in the term of telecommunication. One of these applications is the telemedicine where the patients' digital data can transfer between the doctor…
the impact of medical technology on expansion in health care expenses has long been a subject of essential interest, mainly in the context of long-term outcrops of health spending, which must deal with the issue of the a…
Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. More…
Diabetes is a chronic disease that needs to regularly be monitored to keep the blood sugar levels within normal ranges. This monitoring depends on the diabetic treatment plan that is periodically reviewed by the endocrin…
In this paper, a new classification approach combining support vector machine with scatter search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach is used to find near optim…
An efficient detection of optic disc (OD) in colour retinal images is a significant task in an automated retinal image analysis system. Most of the algorithms developed for OD detection are especially applicable to norma…
The analysis of electrocardiograph (ECG) signal provides important clinical information for heart disease diagnosis. The ECG signal consists of the P, QRS complex, and T-wave. These waves correspond to the fields induced…
