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
The rapid scientific and technological merging be-tween Internet of Things (IoT), cloud computing and wireless body area networks (WBANs) have significantly contributed to the advent of e-healthcare. Due to this the qual…
This paper explores electronic health as a segment of electronic government. International practice in electronic health field and electronic health strategies adopted in Europe are analysed. Current practices in deliver…
The applicability and effectiveness of clustering algorithms had unquestioningly benefitted solving various sectors of real-time problems. However, with the changing time, there is a significant change in forms of the da…
Cost, time and resources are major factors affecting the quality of hospitals business processes. Bio-medical processes are twisted, unstructured and based on time series making it difficult to do proper process modeling…
Electronic Health Record (EHR) is a valuable asset of every healthcare and it needs to be protected. Human errors are recognized as the major information security threats to EHR systems. Employees who interact with EHR s…
This study aims to evaluate the adoption of Cloud Computing in Saudi university hospitals and to investigate the factors that impact the adoption. This study integrates the Technological, Organizational, Environmental (T…
Medical data are extensively used in the diagnosis of human health. So it has played a vital role for physicians as well as in medical engineering. Accordingly, many types of research are going on related to this to have…
Medical image processing is one of the most demanding domains of the computing sciences. The importance of the domain is in terms of the CPU and the memory requirements that shall be used by the system to compute the res…
Nowadays, diabetes disease is considered one of the key reasons of death among the people in the world. The availability of extensive medical information leads to the search for proper tools to support physicians to diag…
Modern world advances in sensors miniaturization and wireless networking which enables exploiting wireless sensor networking to monitor and control the environment. Human health monitoring is promising applications of se…
