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
To diagnose Parkinson’s disease (PD), it is necessary to monitor the progression of symptoms. Unfortunately, diagnosis is often confirmed years after the onset of the disease. Communication problems are often the first s…
Agriculture and modern farming is one of the fields where IoT and automation can have a great impact. Maintaining healthy plants and monitoring their environment in order to identify or detect diseases is essential in or…
The main objective of this work is to enhance the prediction of the Freezing of Gait (FoG) episodes for patients with Parkinson's Disease (PD). Thus, this paper proposes a hybrid deep learning approach that considers FoG…
The growing and marketing of coffee is an impor-tant source of economic resources for many countries, especially those with economies dependent on agricultural production, as is the case of Colombia. Although the country…
In recent years, cloud-based medical record sharing has greatly improved the process of researching the disease and patient diagnosis. However, since cloud systems are centralized, there is serious concern about data sec…
It is paramount to ensure the integrity and authenticity of medical images in telemedicine. This paper proposes an imperceptible and reversible Medical Image Watermarking (MIW) scheme based on image segmentation, image p…
With the introduction of the novel coronavirus and the ensuing epidemic, health care has become a primary priority for all governments. In this context, the best course of action is to implement an Internet of Things (Io…
Small objects detection in medical image becomes an interesting field of research that helps the medical practitioners to focus on in-depth evaluation of diseases. The accurate localization and classification of objects…
Detecting cardiovascular problems during their early stages is one of the great difficulties facing physicians. Cardiovascular diseases contribute to the deaths of around 18 million patients every year worldwide. That's…
The considerable research into medical health systems is allowing computing systems to develop with the most cutting-edge innovations. These developments are paving the way for more efficient medical system implementatio…
