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
Diabetes mellitus stands as a major public health issue that affects millions globally. Among the various complications associated with diabetes, diabetic retinopathy presents a significant concern, affecting approximate…
This paper introduces a novel deep learning framework for highly accurate COVID-19 detection using chest X-ray images. The proposed model tackles the challenge by combining stacked Convolutional Neural Network models for…
Integrating Internet of Things (IoT)-assisted eye-related recognition incorporates connected devices and sensors for primary analysis and monitoring of eye conditions. Recent advancements in IoT-based retinal fundus reco…
Medical image classification is crucial for diagnosis and treatment, benefiting significantly from advancements in artificial intelligence. The paper reviews recent progress in the field, focusing on three levels of solu…
Bioinformatic data concentrated on the accumulation of data pace in the undesired information. Bioinformatics data has vast data-intensive biological information through the computation of data. However, bioinformatics d…
Stroke rehabilitation is fraught with challenges, particularly regarding patient mobility, imprecise assessment scoring during the therapy session, and the security of healthcare data shared online. This work aims to add…
Paddy rice, an essential food source for millions, is highly susceptible to various leaf diseases that threaten its yield and quality. This study introduces a cutting-edge hybrid deep learning model designed to address t…
Depression is common and dangerous if untreated. We must detect depression patterns early and accurately to provide timely interventions and assistance. We present a novel depression prediction method (depressive-deep),…
Agriculture is essential to the world's desire to produce food, generate income, and maintain livelihoods. Citrus fruits are produced worldwide and have a significant impact on food production, nutrition, and agriculture…
Respiratory diseases are one of the most prevalent acute and chronic ailments worldwide. According to a recent survey, there were around 545 million cases of chronic respiratory diseases worldwide. Chronic respiratory di…
