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
Wireless Body Area Network (WBAN) is a collection of wireless sensor nodes which can be placed within the body or outside the body of a human or a living person which in result observes or monitors the functionality and…
This paper proposes a hybrid intelligent system as medical decision support tool for data classification based on the Neural Network, Galactic Swarm Optimization (NN-GSO), and the classification model. The goal of the hy…
X-rays are ionizing radiation of very high energy, which are used in the medical imaging field to produce images of diagnostic importance. X-ray-based imaging devices are machines that send ionizing radiation to the pati…
More people search internet for medical and health information. Due to increase in demand for online health services, hospitals need to equip their websites with usability standards. Hospital websites should be user cent…
Studies demonstrate that monitoring and recording movement of rehabilitation exercises can improve the degree of recovery of the patient. Technologies exist to track user movements but they are often large, expensive, or…
To make the best use of the vast potential opportunities that accompanies medical IoT sensor devices, security and privacy measures are expected to be inculcated as fundamental requirement within these systems. Although…
To improve public health care outcomes with reduced cost, this research proposed a framework which focuses on the positive and negative symptoms of illnesses and the side effects of treatments. However, previous studies…
During the treatment process, medical institutes collect context information about their patients and store it in their healthcare systems. The collected information describes the measurable, risk, or medication informat…
New trends in software engineering are reshaping the computing landscape – computation is increasingly portable, storage is increasingly elastic, and data accessibility is increasingly “always on” and “always available”…
Alzheimer disease (AD) is one of the most common form of dementia. Accurate detection of AD and its initial stage i.e., mild cognitive impairment (MCI) is a challenging task. In this study, a computer-aided diagnosis (CA…
