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
Plant disease identification at an early stage plays a crucial role in ensuring efficient management of the diseases and crop protection. The occurrence of plant ailments can result in substantial reductions in both crop…
In recent years, deep learning has been increasingly used to the detection of pests and diseases. Unfortunately, deep neural networks are particularly vulnerable when attacked by adversarial examples. Hence it is vital t…
In many circumstances, de-identification of a specific region of a biomedical image is necessary. De-identification is used to hide the subject’s identity or to prevent the display of the objectionable or offensive regio…
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The utilization of computer vision technology is of the utmost significance in the examination of plant diseases. Research utilizing image processing to investigate plant diseases necessitates the analysis of discernible…
COVID-19 is a serious infection that cause severe injuries and deaths worldwide. The COVID-19 virus can infect people of all ages, especially the elderly. Furthermore, elderly who have co-morbid conditions (e.g., chronic…
Deep learning applied to computer vision has different applications in agriculture, medicine, marketing, meteorology, etc. In agriculture, plant diseases can cause significant yield and quality losses. The treatment of t…
With the advancement of technology, people are now able to monitor their health more efficiently. Mobile phones and smartwatches are equipped with sensors that can measure real-time changes in blood pressure, SPO2, and o…
Rice is one of the most extensively cultivated crops in India. Leaf diseases can have a significant impact on the productivity and quality of a rice crop. Since it has a direct impact on the economy and food security, th…
